automatic control and robotics syllabi

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Curriculum and Subject Syllabi

Full-time studies in English:

� Automatic Control and Robotics � Electronics and Telecommunication � Computer Science

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A Word from the Dean

The Faculty of Automatic Control, Electronics and Computer Science was founded in 1964, with 250 students and 30 academic staff members. Since then, it has expanded to 4500 students and 230 aca-demic staff members.

From its inception, the Faculty offers courses in Automatic Con-trol, Electronics and Computer Engineering. Initially, the courses had been practically contained in one macro-course and later split into three separate courses.

In the late 90’s, an idea of macro-course was restored. Apart from teaching three separate courses: Automatic Control and Robot-ics, Electronics and Telecommunication, Computer Science, they have been merged together into one macro-course, all taught in English.

It turned out to be an innovative and long awaited for step. The macro-course, three-in-one, teaches skills in the most desirable engi-neering disciplines, in the areas of Robotics, Electronics and Informa-tion and Communication Technologies. Rapid progress in these areas is a challenge of our times. Moreover, the modernized English-taught version of macro-course provides all the necessary professional vo-cabulary, inevitable in today’s engineers’ world.

Our forty years experience and internationally recognized stand-ing will ensure that your M.Sc. degree will be of the highest rank, you will acquire all the skills that international employers are looking for. So, if your interests lay in engineering disciplines and you decide to face a challenge of modern world, do not hesitate and join us. You will be proud to be our graduate. Professor Jerzy Rutkowski

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The Silesian University of Technology; Faculty of Automatic Control,

Electronics and Computer Science offers studies in English:

Macrofaculty of Automatic Control and Robotics,

Electronics and Telecommunication, and Computer Science

Program of these 5-year Master degree studies corresponds to common

standards of technical universities in European countries. This fact makes

possible, for students, to participate in student exchange programs and take

part in semestral or yearly courses in foreign universities as part of their

study programs.

Alumni of Macrofaculty Programme are engineers whose education has

interdisciplinary elements based on three areas listed in the study name,

combined with practical experience and specialized knowledge in one of the

three branches, chosen as leading in the final two years of studies.

During the first three years of studies, students obtain thorough educa-

tion in mathematics, physics, basics of computer sciences and basic technical

sciences: electrical engineering, control theory, electronics, metrology, com-

puter programming, microprocessor systems, databases, computer networks,

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artificial intelligence and computer vision systems. Attention is paid on solv-

ing practical engineering problems, integration of knowledge with team-

work and leading skills. Alumnus acquires skills in using up to date tools of

engineering workshop, in particular CAD and automated design computer

measurements systems, as well as skills in accessing information in scientific

databases. Studies are included in European credit system. Students can eas-

ily participate in student exchange programs and alumni can continue their

education towards PhD both in the same faculty and abroad.

Specializations offered at the end of the studies guarantee a lot of flexi-

bility and follow dynamic changes resulting from scientific developments in

Automation and Robotics, Electronics and Telecommunication and Com-

puter Sciences.

The following specializations are now offered:

Information Processing for Control. Alumnus of this specialization is prepared to work as designer and mainte-

nance engineer of automatic control systems and plants, robotic technolo-

gies, measurement systems, mechatronic technologies and computer systems

of automation.

Computer Aided Information Processing. Alumnus of the specialization Computers and Information Processing is

prepared to carry out research and scientific tasks and to solve engineering

problems in areas of electronic elements and systems design, user hardware

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and software design for systems in electronic and telecommunication, meas-

urements, control and medical equipment.

Databases, Computer Networks and Systems. Alumnus specialized in Databases, Computer Networks and Systems ac-

quires skills in construction, maintenance and usage of system software and

applications development, building systems and computer networks and

designing and administrating of databases operating in various environments

and operation systems.

Alumnus of Macrofaculty is very well prepared to join the work market

in fast changing environment, thanks to creativity, openness to new ideas,

skills in team-work. Proficiency in English and knowledge of English scien-

tific and professional terminology allows him to be employed in interna-

tional companies and in foreign countries.

Undergraduate courses

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Semester 1

Course load (hours per semester) ID Course

L P Lab ECTS

M1.1.1 Algebra and analytic geometry I 30 15 4 M1.2.1 Calculus and differential equations I 45 30 7 M1.3.1 Computer programming I 30 15 5 M1.4.1 Physics I 30 15 4 M1.5.1 Theory of logic circuits I 30 30 6

Semester 2


L P Lab ECTS

M1.1.2 Algebra and analytic geometry II 30 15 5 M1.2.2 Calculus and differential equations II 30 30 6 M1.6.1 Circuit theory I 30 15 3 M1.3.2 Computer programming II 30 30 4 M1.4.2 Physics II 30 15 30 6 M1.5.2 Theory of logic circuits II 30 2

Semester 3


L P Lab ECTS

M1.6.2 Circuit theory II 30 15 15 6 M1.3.3 Computer programming III 30 30 5 M1.7.1 Introduction to electronics I 30 3 M1.8 Introduction to system dynamics 30 15 4 M1.9.1 Numerical methods I 30 3 M1.10 Optimization and decision making 30 30 4 M1.11 Probability and mathematical statistics 20 30 5


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Semester 4


L P Lab ECTS

M1.12.1 Control fundamentals I 45 30 6 M1.13 Digital circuits 30 15 15 5 M1.7.2 Introduction to electronics II 30 30 30 8 M1.14.1 Measurement systems I 30 3 M1.9.2 Numerical methods II 30 3 M1.15.1 Theory of computer science I 30 30 5

Semester 5


L P Lab ECTS

M1.16 Artificial intelligence 30 30 5 M1.17.1 Computer networks I 30 30 6 M1.12.2 Control fundamentals II 30 3 M1.14.2 Measurement systems II 30 4 M1.18.1 Microprocessor systems I 30 15 4

M1.19 Signal processing and communication 30 30 5

M1.15.2 Theory of computer science II 30 3

Semester 6


L P Lab ECTS

M1.20 Computer graphics and vision I 30 30 5

M1.21.1 Data bases I 30 30 6 M1.22 Electromechanical devices 30 15 4

M1.23 Management 30 30 project 4

M1.18.2 Microprocessor systems II 15 30 5 M1.24.1 Operating systems I 30 30 6

Postgraduate courses

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Information Processing for Control - Semester 7

Course load (hours per semester) ID Course L P Lab

ECTS

M2.1 Adaptive systems in control 30 15 4 M2.2 CAD of control systems 30 30 project 5 M2.3 Computer controlled systems 30 15 4 M2.4 Hierarchical control 30 30 5 M2.5 Robot vision 30 30 6 M2.6 Robotics 30 30 6


Course load

(hours per semester) ID Course L P Lab

ECTS

M2.7 Advanced control 45 30 15 7 M2.8 Computer integrated manufacturing 30 15 5 M2.9.1 Programmable controllers I 30 30 6 M2.10 Quality control 30 15 3 M2.11 Reliability and intrinisic safety 15 15 3 M2.12 Sensors and actuators 45 30 6 Industrial training 4 weeks 0


Course load


ECTS

M2.13 Applied digital signal processing 30 15 3 M2.14 Biotechnical systems 30 15 3 M2.15 Estimation and identification 45 30 6 M2.16 Expert systems 30 30 4 M2.17.1 Final project seminar I 30 3 M2.18 Graphical programming 15 8 1.5 M2.19 Modelling and simulation 30 30 5 M2.9.2 Programmable controllers II 30 project 3 M2.49 Advanced Image Processing 15 7 1.5


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Computer Aided Information Processing - Semester 7


ECTS

M2.20.1 Analog circuits design I 30 30 15 6 M2.21 Computer aided electronic circuits design 30 15 3 M2.22.1 Digital circuits design I 30 15 30 6 M2.23 Electromagnetic field theory 30 30 5 M2.24 Theory of information and coding 30 2 M2.25 Information knowledge processing 30 2 M1.18.3 Microprocessor systems III 15 project 2 M2.26 Radiocommunication 30 15 4


Course load


ECTS

M2.20.2 Analog circuits design II 30 30 7 M2.27 Bionics 30 15 4 M2.50 Computer networks II 30 2 M2.22.2 Digital circuits design II 30 30 7 M2.28.1 Exchange devices I 30 2 M2.29 Java and programming in the Internet 30 30 4 M2.30 Medical information systems 30 2 M2.31 Wireless computer networks 30 2 M2.51 Cellular phone systems 30 2


Course load


ECTS

M2.32 Digital and analog telecommunication 30 15 15 6 M2.28.2 Exchange devices II 45 4 M2.33.1 Final project seminar I 30 2 M2.34 FPGA and digital processing 30 30 4 M2.35 Microelectronics 30 30 5 M2.36 Optoelectronics 30 15 5 M2.37 Programmable logic devices 30 15 4


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Databases, Computer Networks and Systems - Semester 7


ECTS

M2.35 Algorithm and Data Structures 30 30 6 M2.36.1 Computer architecture I 30 2 M1.21.2 Data bases II 30 30 6 M2.37.1 Digital modelling and simlation I 30 30 4 M1.18.3 Microprocessor systems III 30 project 3 M1.24.2 Operating systems II 30 30 5 M2.38.1 Programming in assembler I 30 2 M2.39.1 Software engineering I 30 2


Course load


ECTS

M2.36.2 Computer architecture II 30 3 M1.17.2 Computer networks II 30 30 6 M2.40.1 Concurent programming I 30 30 4 M2.37.2 Digital modelling and simulation II 30 3 M2.41 Introduction to compilers 30 2 M2.29 Java and internet programming 30 30 4 M2.38.2 Programming in assembler II 30 3 M2.39.2 Software engineering II 30 3 M2.31 Wireless computer networks 30 2 Industrial training 4 weeks 0


Course load


ECTS

M2.43 Computer graphics and vision II 30 30 6 M2.40.2 Concurent programming II 30 3 M2.44 DBMS Oracle 30 30 4 M2.45 Distributed computer systems 30 30 5 M2.46 Industrial networks 15 15 2 M2.47 Programming for Windows 30 30 6 M2.48 Windows Networks Administration 30 30 4 M2.50 Stochastic Simulation 15 15 2


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All specializations - Semester 10


L P Lab ECTS

M2.33 Final project seminar 30 2 Master dissertation 28



Semester L P Lab ECTS

M1.1.1 Algebra and analytic geometry I 1 30 15 4 M1.1.2 Algebra and analytic geometry II 2 30 15 5

Lecturer: Iwona Nowak

Objectives of the course

The objective of the course is to present the fundamentals of linear algebra and analytic geometry and to indicate the approaches for find-ing solutions to algebraic and geometric problems arising in other branches of mathematics and technical applications.

Course description

Complex Numbers: complex number def., algebraic form, the com-plex plane, operations on complex numbers, modulus, complex conju-gate and its properties, division, polar form, DeMoivre’s Theorem, nth roots, complex exponents. Polynomials: roots of polynomials, factorization, Fundamental Theo-rem of Algebra Matrices: definition, operations on matrices (addition, scalar multipli-cation, matrix multiplications), identity matrix, transpose of a matrix. Determinants: def., properties of the determinants, evaluating deter-minants by row reduction, cofactor expansion, elementary row/column operations. Matrices cont.: inverse of a matrix, finding the inverse of matrix by Gauss-Jordan Elimination and by its Adjoint, properties of inverses. Systems of Linear Equations: def., Gaussian Elimination with Back Substitution, Gauss-Jordan Elimination, Cramer’s Rule, homogenous systems of lin. eq., rank of matrix, Kronecker-Capelli’s Theorem. Vectors in 3D Space: vectors in coordinate system, operations, dot product, orthogonal projection, cross product, scalar triple product of vectors.


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Planes and Lines in 3D Space: plane equation, positions of two planes, distance from the point to the plane, equations for line in 3D space, positions of two lines and distance between two lines Conic Sections and Quadric Surfaces Vector Spaces: subspecies, linear independence, basis and dimension, inner product spaces, orthogonal basis, Gram-Schmidt process. Complex Vector Spaces: Linear Transformations: kernel and range, matrices of linear transfor-mations, inverse linear transformation, transformation matrix for non-standard basis, transition matrices and similarity Eigenvalues and Eigenvectors: Diagonalization, orthogonal Diago-nalization, orthogonal matrices, Jordan canonical form Quadratic Forms: problems involving quadratic forms, diagonalizing quadratic forms, application to conic sections and quadric surfaces Applications of linear algebra: to computer graphics, cryptography, computer tomography and such.



M1.2.1 Calculus and differential equa-tions I 1 45 30 7

M1.2.2 Calculus and differential equa-tions II 2 30 30 6

Lecturer: Ewa Łobos

Course description

The real number system – the real line – the absolute value. The concept of a function; examples. Metric on a set – metric spaces. One-to-one onto functions; composite functions, inverse functions. Review of elementary functions; hyperbolic and inverse trigonometric functions. Sequences. Convergence in a metric space. Properties of


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convergent sequences. Limits of some numerical sequences: n

n)(

11 + ,

n n , n a , !n

a n

. The limit of a function defined on a metric space.

Properties of limits. Continuity – discontinuity – properties of continuous functions. Asymptotes. The derivative of a function – definition, interpretations. Tangent line. Differentiation formulae and rules. Higher derivarives. Differentials – definition, applications. Parametric equations, derivation of parametric equations. Fermat’s theorem. Rolle’s theorem. The Lagrange theorem. Cauchy’s theorem. L’Hospital’s rules. Taylor’s formula. Approximation by the Taylor polynomials. Critical points and extreme values – the first derivative test. Concavity and inflections – the second derivative test. Sketching the graph of a function. Antiderivatives and indefinite integrals. Techniques of integrations – integration by parts, the method of substitution, integration of rational functions by partial fractions, rationalizing substitutions. The definite integral – definition, properties. Fundamental theorems of calculus. Applications (area between two curves, arc length). Ordinary differential equations. A solution (general, particular, singular). Initial-value and boundary-value problems. Separable equations. First order linear differential equations. Linear independence of functions and Wronskian. Second order linear differential equations with constant coefficients. The characteristic equation. The method of undetermined coefficients, the method of variation of parameters. Linear equations of order n with constant coefficients. The Laplace transformation – properties, computations, application in differential equations. Functions of several variables. Partial derivatives. Tangent plane. The total differential – definition, applications, differentiability. The chain rules. Implicit functions. Directional derivative and gradient vector. Extrema. Double and triple integrals – definitions, properties, basic theorems and applications. Change of variables (polar, cylindrical and spherical coordinates). Line inegrals. Green’s theorem.


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Infinite series. The sum of an infinite series. Series of nonnegative terms – the comparison, ratio and root tests. Alternating series. Absolute and conditional convergence. Power series. Term-by-term differentiation and integration. Taylor’s and Maclaurin’s series. The Fourier series.

Course load

(hours per semester) ID Course Semester L P Lab

ECTS

M1.3.1 Computer programming I 1 30 15 5 M1.3.2 Computer programming II 2 30 30 4 M1.3.3 Computer programming III 3 30 30 5 Lecturers: Roman Starosolski , Piotr Fabian Objectives of the course

The aim of the course is to lay a solid foundation of good software engineering and programming language practice. Course description

The course provides the knowledge required to understand, design and write computer programs in C and C++. The program contains: intro-duction to imperative programming in C/C++ language (basic knowl-edge required to create and understand programs as well as skills es-sential for good software engineering and programming practice), ba-sic algorithms and data structures, substantial knowledge on object-oriented programming using C++, and some advanced problems and techniques essential for programmers, exceeding traditional programs of elementary programming courses by giving some knowledge in-volving the latest achievements in software technology. Lectures are illustrated with slides with many sample programs. They are sup-ported by laboratories, during which students have an occasion to cre-ate programs on their own.


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M1.4.1 Physics I 1 30 15 4 M1.4.2 Physics II 2 30 15 30 6

Lecturer: Jacek Szuber


To acquaint the students with main physical concepts and their appli-cations in modern science and technology. Course description

Fundamentals laws of kinematics and dynamics of material points. Inertial and non-inertial motions. Fundamental laws of kinematics and dynamics of rigid body. Conservative principles in motion. Energy and power in mechanics. Conservative principles Mechanical vibrations. Pendulum. Differential equation of vibration. Simple, damped and damped and forced vibrations. Wave motion. Wave traveling in one dimension. Huygen's principle: laws of reflec-tion and refraction. Superposition of waves. Sound waves. Doppler effect. Thermal properties of gases - gas transitions. Equation of state of an ideal and real gases. Microscopic theory of gases - Boltzmann equa-tion. Maxwell-Boltzmann distribution. Gas pressure in the atmos-phere. Botzmann distribution. First law of thermodynamics for proper transitions. Second law of thermodynamics. Carnot Cycle. Gravitational field: source, Newton’s force, strength, potential and energy. Electrostatic field: sources, Coulomb's law, flux, strength, potential and energy. Magnetic field: sources, forces, flux, strength - Ampere's law and Biot-Savart law. Electromagnetic induction. Faraday's law and Lenz's rule. Inductance and self-inductance. Energy in magnetic field. Max-well's equations.


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Electromagnetic radiation. Wave nature of radiation. Fermat's princi-ple. Thermal radiation - blackbody model. Theory of Wien, Rayleigh-Jeans. Planck's hipothesis - quantization of electromagnetic radiation. Photoelectric effect, interaction of light with gravity, X-Ray spectrum, Compton effect Wave-particle duality - de Broglie hipothesis - electron diffraction. Fundamentals of quantum mechanics. Heisenberg uncertainty princi-ple. Wave function of matter. Schroedinger equation and its applica-tion. Hydrogen spectrum - Balmer's experiment and Rydberg formula. Classical atomic models - Bohr postulates. Quantum model of hydro-gen atom. Electron energetic states. Zeeman effect. Electron spin - Stern-Gerlach experiment. Quantum numbers. Pauli principle. Peri-odic table of elements. Atomic structure of solid state. Chemical bonds in crystals. Electronic band structure of solid state. Fundamentals of semiconductor physics. Physical basis of microelectronics and nanoelectronics.



M1.5.1 Theory of logic circuits I 1 30 30 6 M1.5.2 Theory of logic circuits II 2 30 2 Lecturer: Krzysztof Cyran Course description

Introduction to switching circuits theory- basic concepts, Boolean al-gebra and its theorems, algebraic operations and operators, function-ally complete systems, gates, implementation of logic functions using different gates, types of switching circuits. Forms of Boolean functions (canonical, reduced, irredundant), truth tables, transformations, Karnaugh maps, minimization, examples of combinational switching circuits. Hazards – static and dynamic. Binary numbers, codes, translators, encoders and decoders


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Multiplexers and demultiplexers (simple and advanced circuits) Iterative switching circuits (adder, substractor, comparator, etc.) Asynchronous static sequential circuits – structures, types of program specification, basic asynchronous flip-flops – timing charts, excitation tables Huffman’s method – the flow table, reduction, coding (critical and non-critical race, essential hazard, hazards), determining the flip-flop excitation functions. Synchronous sequential circuits – structures, program specification, designing, synchronous flip-flops, triggering ways Registers and counters – disigning, frequency dividers Microprogrammable circuits (different structures, optimization). Circuits with delay units Design with progammable logic devices PLDs (PROM, PAL, PLA)



M1.6.1 Circuit theory I 2 30 15 3 M1.6.2 Circuit theory II 3 30 15 15 6 Lecturer: Jerzy Rutkowski Objectives of the course

The aim of this introductory course is to lay down some important foundations of circuit theory and analysis for subsequent use in later courses, such as Signal Theory and Electronics Fundamentals. Course description

Introduction The revision of some general definitions, such as voltage, node volt-age, current, electric power and energy. D.C. Analysis General terms and definitions: general classification of circuit ele-ments and their description; Ohm's law; principles of current and volt-age arrow placement; circuit diagram, presentation of circuit topology


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by means of its graph and definition of graph elements such as node, branch, cutset and loop; Kirchhoff's Current Law and Kirchhoff's Voltage Law; electric energy and power: energy conservation law and power balance; voltage, current and power calculations for simple circuits - practical examples. Linear Circuits Series/parallel connection of resistors, voltage/current divider; real source, Thevenin's and Norton's equivalent diagrams; voltage, current and power calculations for complex circuits by means of Kirchhoff's laws and Ohm's law - generalized Kirchhoff's method; node voltage method (Coltri's method) ; superposition theorem; passive and active two-terminal sub circuit; Thevenin theorem and Norton theorem; ma-ximum power transfer; separation principle; calculation/measurement of power transmitted from one multi-terminal sub circuit to another; multi-terminal elements (passive and active), their description and voltage/current/power calculations for circuits containing such ele-ment(s); two-port element as a special case of multi-terminal element; dependent sources, description of a three-terminal/two-port element by means of such sources; sensitivity analysis: introduction of basic definitions and terms such as absolute and relative sensitivity, toler-ance region and acceptability region; calculation of circuit function deviation caused by design tolerances Nonlinear Circuits graphical method: analysis of circuit containing only one nonlinear element and construction of total characteristic of elements connected in series/parallel; piecewise linearization method (analysis of medium size circuit with possibly multiple solutions); large nonlinear circuit analysis - iterative method (Newton-Raphson method) Transient analysis real circuit and simplifying assumptions ; ideal energy dissipating and energy storage elements; definitions and time-domain u-i relationships for resistor, capacitor, coil (self inductance) and mutual inductance; Kirchhoff's laws and Ohm's law in time domain; analysis of RL circuit in time domain (classical approach); Laplace transform: definition and basic properties; introduction of Heaviside's function (step function) and Dirac's function (impulse function); element equations and circuit laws in Laplace operator domain; transient responses of RC and RL circuits with step input; boundary values based analysis of the 1st or-


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der circuits with zero initial conditions; analysis of the 2nd order cir-cuits with zero initial conditions: Heaviside's formula; detailed analy-sis of the series RLC circuit; analysis of circuits with non-zero initial conditions, superposition of responses (natural and forced response); transfer function in time and operator domain, ideal and practical inte-grator and differentiator; calculation of responses for complex inputs (other then step inputs), such as rectangular pulse (ideal and real) and others A.C. Analysis description of a periodic function: average value, rms value; introduc-tion to the phasor (complex) description of a function; complex func-tion in time-domain and complex rms function in frequency domain; Kirchhoff's laws and element equations (for ideal elements) in fre-quency domain; introduction of phasor diagrams, phasor diagram that matches a circuit topology; algorithm of A.C. analysis based on phasor-complex calculations; calculation of transient sinusoidal re-sponse for the 1st order circuit; power and energy: instantaneous, re-active, apparent and active power; power factor and its correction; passive two-terminal sub circuit: introduction of impedance (resis-tance and reactance) and admittance (conductance and susceptance); maximum power transfer; real inductor and capacitor: equivalent dia-grams and frequency analysis; introduction of transfer function in fre-quency domain; frequency characteristic, amplitude and phase charac-teristics; amplitude characteristic in logarithmic scale - Bode plot; series and parallel resonance (LC/RLC and LC/GLC): definition of resonant frequency, bandwidth and Q-factor, voltage and current phasor diagrams; resonance in arbitrary two-terminal sub circuit; fre-quency filters: definition of bandwidth, classification and the simplest practical realizations; mutual inductance M in AC circuit: two-port equations in phasor (frequency) domain; transformers: ideal and air-core: two-port equations and schemes; coil with ferromagnetic core and transformer with ferromagnetic core: diagrams for low, medium and high frequencies; 3-phase network: connections, analysis and power measurement; Circuits with constants uniformly distributed, transmission line Circuits with lumped constants have been discussed so far. For such circuits functions (voltage, current, etc.) are functions of time, exclu-sively. In this Part circuits with constants uniformly distributed are


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discussed. For such circuits all functions are functions of two vari-ables: time t and place x. The most typical case of such circuit is a transmission line. The following subjects related with a transmission line are contained in this part: two-pole equations in time domain and in operator domain; introduction of line parameters: characteristic impedance, propagation constant, reflection coefficients; transient response of line with zero initial conditions, step and arbitrary a peri-odical (pulse) input: general and special cases (distortion less and loss less line, infinite length/matched load line); AC analysis, standing waves, input imedance



M1.7.1 Introduction to electronics I 3 30 3 M1.7.2 Introduction to electronics II 4 30 30 30 8 Lecturer: Zdzisław Filus


To provide a basic understanding of the operating principles of semi-conductor devices and an introduction to the theory and operation of electronic circuits

Course description

Introduction: definitions and basic features of analog and digital sig-nals and circuits. Resistors, capacitors, inductors and transformers. Logarithmic scale and Bode plots. Basic RC circuits. Intrinsic and extrinsic semiconductors. P-N junction: charge density, electric field and voltage distribution, contact potential, capacitance of the junction, V-I characteristics, switching characteristics. Various types of diodes: Zener and avalanche effects, varicaps, Schottky diodes. Bipolar tran-sistors: principle of operation, basic characteristics and parameters, Ebers-Moll model, linear piecewise models, small-signal equivalent


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circuits, switching characteristics, biasing circuits, basic amplifiers: CE, CB and CC, current sources, current mirror. Field-effect transis-tors: operation of JFETs and MOSFETs, voltage-to-current character-istics, biasing circuits, basic amplifiers (CS, CG, CD), current sources, analog switches, NMOS and CMOS gates. Optoelectronic devices: photoresistor, photodiode, light emitting diode, optocouplers, displays. Simplified theory of feedback: types of feedback systems, influence of negative feedback on gain, input and output impedances, bandwidth, noise reduction, stability, gain and phase margins. Power amplifiers: class A, B, C amplifiers, principle of operation, efficiency. Differen-tial amplifier: large and small-signal analysis. Operational amplifiers: ideal and non-ideal amplifier, basic applications. Integrators and dif-ferentiators. Analogue comparators. Sine wave oscillators. Square wave and ramp oscillators. Rectifier systems. Regulated power sup-plies: IC voltage regulators, switching regulators. Sample & hold cir-cuits. Analogue-to-digital and digital-to-analogue converters: basic methods of conversion and their comparison.



M1.8 Introduction to system dy-namics 3 30 15 4

Lecturer: Andrzej Pola�ski Objectives of the course

Objectives of the course are twofold. First it is intended that students get some experience in the field of constructing mathematical models for various applictations. Second students learn basic tools of analysis of dynamical systems and some facts about classification of their pos-sible behavior.


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Course description

As an introduction, the course starts with the overview of some meth-ods of building mathematical models in several areas: mechanics, mechanotronics, electronics, chemical process dynamics, ecology, genetics. It is demonstrated that mathematical modeling of dynamic behavior of systems leads to ordinary differential or difference equa-tions or partial differential equations. In the subsequent parts of the course the interest is focused on systems described by ordinary differ-ential and difference equations. Several properties and types of dy-namic systems are studied. In the first part method of deriving motion equation by balances is presented. Several types of balances are over-viewed and examples in many areas are provided. The concept of state variables, inputs outputs and constant or time variable parameters is introduced. Construction of state – space models for electrical systems with voltage across capacitors and currents through inductances, is shown. The application of variational principles to dynamic systems modeling is then introduced. The method of Lagrange Equations is presented and its interpretation on the ground on variational theory and Hamilton principle is given. Rules of computing potential and kinetic energies and dissipation power of typical elements of dynami-cal systems are presented. Many examples are studied in mechanics, electronics, mechatronics etc. Electromechanical analogies are then discussed. Two types of electromechanical analogies are presented. The first type, based on correspondences between types of energies leading to current – velocity and voltage – force analogies and second type, based on diagrams correspondences leading to voltage – velocity and current – force analogies. Some approaches to solving and analyz-ing dynamic equations are presented. Method of state space and iso-clines is derived. Approximate analysis around equilibria, by lineari-zation, is presented. Solvable models and models solvable by quadra-tures are discussed and the role of analytical methods in dynamical systems analysis is highlighted. First integrals of systems are defined and examples are given of their use. The method of eliminating part of system variables by using first integrals is presented. Methods of sim-plifying model equations by using symmetries and approximations are shown. Linear dynamical systems and their solutions are presented. Perturbations and singular perturbation methods of approximate analysis of nonlinear systems dynamical behavior are shown. Method


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of averaging for approximate description of nonlinear oscillations is derived. Finally some examples of dynamical systems with distributed parameters are presented.



M1.9.1 Numerical methods I 3 30 3 M1.9.2 Numerical methods II 4 30 3 Lecturer: Jerzy Klamka


To provide an overview of different numerical methods with several examples. Course description

Theory of errors. Types of errors. Absolute errors. Relative errors. Errors of algebraic computations. Computation of values of the functions. Definition of analytical func-tion of real variable. Taylor and Maclaurin series expansions. Errors of series expansions. Interpolation. Formulation of the interpolation problem. Geometric interpretation. Lagrange’a interpolation polynomial. Newton’s inter-polation polynomial. Linear difference operators, their properties and computations methods. Newton’s interpolation polynomial with dif-ference operators. Errors of interpolation. Relationships between dif-ferent interpolation polynomials. Examples. Numerical differentiation. Differential operators and their connections with difference operators. Formulas for numerical differentiation. Ex-amples. Numerical integration. Formulation of numerical integration. Newton-Cotes formula for numerical integration. Other numerical integration


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methods. Relationships between different integration methods. Exam-ples. Approximation. Formulation of the approximation problem. Different types of approximation. Space of square integrable functions. Least square approximation method. Examples of orthogonal and orthonor-mal bases. Point approximation. Uniform approximation in the space of continuous functions. Tchebyshev polynomials and their applica-tion in uniform approximation. Examples. Solution of systems of linear equations. Systems of linear equations and ots solution. Algorithm of Gauss elimination method. Examples. Iterative methods. Eigenvalues and eigenfunctions. Definitions of eigenvalues and ei-genvectors. The method of finding the greatest real eigenvalue and corresponding eigenvector. Examples. Approximate solution of nonlinear equations. Approximate intervals methods. Newton's method. Examples. Bernoulli method. Examples. Approximate solution of ordinary differential equations. Taylor’s method. Piccard’s method. Runge-Kutty method. Examples. Approximate solution of partial differential equations. Discrete method for parabolic type partial differential equation. Line method for parabolic type partial differential equation. Approximate solution of the integral equations. Approximate solution of the integral Fredholm-Volterra equation. Neumann’s method. Ex-amples.



M1.10 Optimization and decision making 3 30 30 4

Lecturer: Andrzej �wierniak


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This course is concerned with optimization theory and computational methods with special emphasis on their application in optimizing de-sign and decision making. It concentrates on methodology of obtain-ing minimizing or maximizing solutions and developing numerical algorithms supporting this process.

Course description

The main idea of this course is that a major part of optimization theory could be unified by a number of concepts and theorems from theory of vector spaces. They allow solve some crucial and complex infinite dimensional problems including those arising in consideration of time dependent functions as it is the case in optimal control design. Simple and intuitional interpretation of both static and dynamic systems is possible due to functional analysis - a science about linear vector spaces. The first part of the course is just the minimal introduction to the functional analysis and more precisely to its branch related to op-timization techniques. Using this very introduction it is possible to formulate some necessary conditions for optimality of solution to some unconstrained and constrained problems. This enables in turn to specify some efficient methods in algorithms in the paticular optimi-zation problems by simply choosing the space in which the general result should be applied. For example the standard necessary condition of the unconstrained extrema of a differentiable functionals enables to solve classical variational problems and leads to Euler-Lagrange equa-tions. On the other hand the use of two Lusternik theorems opens a possibility of derivation of the general Kuhn-Tucker conditions and offers a very good interpretation for Lagrange multipliers, costate variables, izoperimetric problems for a number of different con-strained optimization problems. Of course some results and algorithms typical for very specific problems should be treated separately. This is for example the case of standard linear or nonlinear programming methodology including Simplex algorithm and its "successors". The model of the controlled plant is treated as a number of constraints im-posed on the optimization problem and resulting Hamiltonian optimi-zation conditions are interpreted in view of general Lagrange or Kuhn-Tucker conditions. Then by extending the space and class of possible


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functions the students are led to the Pontryagin maximum principle. For the tractability only the simple extensions are presented including problems with fixed, free and moving terminal point, fixed or free terminal time for systems described by ordinary differential or differ-ence state equation with piecewise continuous control functions and additional constraints imposed only on the values of control variables. It allows however to demonstrate efficiency of this methodology on a number of standard and real-world problems including linear-quadratic problems, time-optimal problems, optimal harvesting prob-lems etc. The special attention is paid to the Bellman's principle of optimality and resulting techniques of dynamic programming. The course contains derivation of Bellman's equations basing on the prin-ciple of optimality for both discrete-time and continuous-time systems and focus attention on a number of their possible applications includ-ing once more linear-quadratic problems, resource allocation, grid techniques and a variety of flow problems in networks. The lecture is supplied by the computer laboratory. This part of the course is devoted to the most popular numerical optimization algoritms. Once more the unified approach in derivation of the whole family of gradient type and Newton type algorithms is very helpful. Of course it is appended by an analysis of computational properties of the algorithms specified for the specific problems.



M1.11 Probability and mathemati-cal statistics 3 30 30 5

Lecturers: Marek Kimmel, Joanna Pola�ska Objectives of the course

The objective of this course is to give a theoretical basis of probabil-ity theory and statistics in very general context and to demonstrate the


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possible applications of this theory to applied models in system engi-neering, in operation research, and time series.

Course description

The course consists of two parts: probability theory and mathematical statistic. The probability part starts with set theoretic concepts such as sigma-algebras, and denumerable operations on sets. Then, probability is introduced as a denumerably additive nonnegative normed set func-tion. Properties of probabilities, including conditional probability fol-low. Random variables are introduced as measurable maps from the probability space in to the set of real numbers with Borel sigma-algebra. Distribution functions are discussed, including important ex-amples of continuous and discrete distributions binomial/Poisson, geometric, uniform, exponential, normal, multivariate normal, gamma and chisquare). Independence of events is shown to lead to strong re-sults such as Borel-Cantelli theorems and Kolmogorov 0-1 law. Ex-pected values are defined as Lebesgue integrals of random variables. Monotone and Dominated Convergence theorems follow. Law of Large Numbers and Central Limit Theorem are discussed (with proofs sketched). Convergence of random variables (in distribution, in prob-ability and with probability 1) is illustrated by examples. Finally, time-discrete and time-continuous Markov processes and Poisson processes are introduced, illustrating more general notions such as limit and stationary distributions, waiting times and so forth. The second part starts with the survey of the methods of simple statis-tical testing where special emphasis is put on the hypothesis tests for the mean and variance of a normal population. Then the nonparamet-ric methods are introduced followed by the ANOVA algorithms. Next we focus on the way of describing the relations among random vari-ables. We introduce the measures of correlation (for both Gaussian and non – Gaussian random variables) and basic statistical tests. Then we give a general introduction to linear regression and consider the estimation problem for unknown parameters of probability distribu-tion. Here we discuss the following three main methods: maximum likelihood method, the least squares method and the method of mo-ments. Finally we present the basis of the analysis of frequencies.


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All the theoretical material is broadly illustrated by the examples whose purpose is to help understanding the theoretical concepts and to show the possibility of applications of the probability methods in en-gineering practice.



M1.12.1 Control fundamentals I 4 45 30 6 M1.12.2 Control fundamentals II 5 30 3 Lecturer: Ryszard Gessing Objectives of the course

To give a basic knowledge which are needed in majority of the courses in Automation and Robotics as well as useful in Electronics and Telecommunication and in Computer Science Programs of Study.

Course description

Feedback control systems, examples and basic notions, dynamic and static elements, block diagrams. Mathematical models of dynamic systems: differential equations, state equations and their linearization, transfer functions, time and frequency responses, relations between different models. Steady state characteristics. Basic dynamic elements. Dynamic system properties. Solution of the stationary state equations, fundamental matrix. Controllability and observability and their rela-tion with transfer function and minimal realization description. Stabil-ity of linear systems, Hurwitz stability criterion. Control systems structure. Closed loop system description. Feedback systems proper-ties: disturbance influence compensation, dynamic properties shaping, characteristics linearization. Feedback, feedfarward, combined and cascade systems. Block diagrams transformations. Closed-loop sys-tems stability. Characteristic equation, use of the Hurwitz Criterion. Nyquist criterion, its derivation and application using Nyquist, Bode


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and Nichols plots. Stability of the systems with delay. Quality of the Control. Time response specifications: steady state error, overshot, settling time. Steady state analysis. Method basing on roots placement, stability degree. Root-locus method. Linear quadratic method, meth-ods basing on frequency responses-applying to control systems de-sign. Compensators, regulators P, PI, PD, PID, regulator parameters tuning. Multivariable systems and their description using state equa-tions and matrix transfer functions. Stability, characteristic equation of the closed-loop system, stability analysis and conditions. Pairing of inputs and outputs. Multivariable systems design. Linear discrete-time systems. Z – transform and its applying to systems description. Dis-crete-time transfer functions. Stability and its analysis, stability condi-tions. Continuous-time versus discrete-time systems.



M1.13 Digital circuits 4 30 15 15 5 Lecturer: Wojciech Sakowski


The aim of the course is to instruct the students in structures of digital integrated circuits and their applications in digital systems design.

Course description

Basic information about digital signals: quantization and coding, bi-nary codes, binary coded decimal numbers (BCD), fixed point posi-tive and negative numbers, symbolic data representation. General de-scription of digital integrated circuits: scale of integration, digital cir-cuits families. TTL family: structures and parameters of basic gates, immunity to interference static and pulse noise margins, comparison of TTL integrated circuits with ECL, CMOS and BiCMOS devices; basic operation and characteristics of TTL and CMOS gates.


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Basic combinational circuits: complex gates, multiplexors, decoders. Sequential circuits: flip-flops, registers, shift registers with feedback, counters. Arithmetic circuits: adders and subtractors for binary and BCD Excess 3 numbers, number comparators, multipliers, floating point arithmetic. Memories: static and dynamic RAMs, ROMs, UVEPROMs, EEPROMs, Flash memories. Programmable logic de-vices: FPLA, PAL, FPGA. Control unit design: hardwired control units, microprogrammed control units. Introduction to FPGA and ASIC design methodologies and hardware description languages. Data input: keys, keyboards. Data output: LED and LCD displays, structure of data displaying circuits. General rules of data transmission: struc-ture of digital system, asynchronous serial and parallel data transmis-sion, handshaking, buses. Long transmission line effects and line ter-minators.

The problems presented during lecture will be illustrated by means of selected examples solved by the person leading the classes.

The practical digital devices will be designed and built in the Design-ing of Digital Devices Laboratory which is equipped with digital modules and racks with power suppliers.



M1.14.1 Measurement systems I 4 30 3 M1.14.2 Measurement systems II 5 30 4 Lecturer: Jerzy Fr�czek


To acquaint the students with measurement systems.


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Course description

Introduction: scope of lectures, literature; integration of intrinsically safe field instrumentation into industrial communication networks; intelligent sensors; institutions: IMEKO, IFAC, EUROSENSORS, PSST – Polish Society of Sensors Technology, COE – Optoelectronic and Electronic Sensors. Smart sensors: Measurement of fluid flow by means of pressure dif-ferential devices - orifice plates and Venturi tubes. Smart interface. The essential sub-systems; list some of the main sensor defects. Zener Barriers (Ex). The general measurement system: purpose, general structure,. ele-ments of system. Definition of sensor; sensor classifications. Example: “Weight measurement system” – elements of system; strain gauges (conventional and silicon). Vocabulary of Basic and General Terms in Metrology: static char-acteristics - range, span, zero, zero drift, sensitivity, resolution, re-sponse, linearity, hysteresis, calibration, accuracy; dynamic character-istics. Specialized measurement system: gas chromatography – column, carrier gas, solid particles, thin layer of liquid composition, HETP – Height Equivalent to a Theoretical Plate, chromatogram, retention time. Detectors: TCD – Thermal Conductivity Detector (katharome-ter), FID – Flame Ionisation Detector, ECD – Electron Capture Detac-tor. Non–Dispersive Infra-Red (NDIR) gas analyser: IR transmission characteristics, one path system, two path system, IR emitters, rotat-ing chopper disc, reference cell, sample cell, radiation detectors (se-lective or non-selective), transfer equation. ITS-90 – The International Temperature Scale of 1990: triple points, freezing points, melting points, interpolation instruments – platinum resistance thermometer, gas and vapour thermometers, ra-diation pyrometer; interpolation equations; thermodynamic (Kelvin) and empirical (Celsius) scales. Thermal radiation measurement system: high temperatures, mov-ing body, temperature distribution over a surface; “black body”, Planck’s law, emissivity of real body, characteristics of transmission medium; general form of thermal radiation measurement system, opti-cal focusing system without and with lens, transmission characteris-


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tics, detectors – thermopiles, bolometers; total detected power, output signal. Pressure (pneumatic) measurement system: elements of system; metal resistance Strain Gauge - tensile stress, compressive stress, lon-gitudinal strain, transverse strain, elastic modulus, Young’s modulus, Poisson’s ratio, GF – Gage Factor; characteristics of system. Review of sensors: conventional, thick, thin and semiconductor tech-nologies; Strain Gages, Zirconia Cell (ZrO2), magnetic (mechanical) sensors, electromagnetic sensors, chemical sensors, gas sensors, resis-tance and thermocouple sensors. Reliability of measurement systems: reliability, unreliability, MTBF - Mean Time Between Failures, failure rate, variation of failure rate during lifetime of equipment – “bathtub” curve, reliability of a system of n elements in series or cascade, availability, methods of improving the reliability of measurement systems.



M1.15.1 Theory of computer science I 4 30 30 5

M1.15.2 Theory of computer science II 5 30 3

Lecturer: Krzysztof Trocki Course description

Algorithms. Definition of an algorithm; Ways of describing algo-rithms; Criteria for comparing algorithms (time and space complexity) Turing machine. Concept of a reasonable computing machine; Tur-ing machine; Universal Turing machine; Formal grammars. Definition of formal grammars; Classification of formal grammars; Grammar of the Reverse Polish Notation; Basic components of a computer. Major levels of computer design; - Components of the machine W;


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Von Neumann's architecture, introduction to the machine W. Von Neumann's architecture; Introduction to the organization of the ma-chine W Designing program control unit and instruction set for the ma-chine W. Designing instruction set for the machine W; Micropro-grammed and hardwired implementation of the program control unit; Designing the program control unit for the machine W Programming in assembly language of machine W. Addressing arrays with the use of self-modifying programs Input / Output functionality. General architecture of input / output devices; Input / output module; Interrupts; Direct Memory Access; - Evolution of input / output functions System software. Assembler; Compiler Management of resources and synchronization. Safety analysis (Data corruption); Liveness analysis (Deadlock); Classical problems of synchronization



M1.16 Artificial intelligence 5 30 30 5 Lecturer: Ewa Straszecka Course description

What is Artificial Intelligence. Methods of AI problems represen-tation. Human and artificial intelligence - similarities and differences. Definitions and branches of AI. A scheme of AI history. AI nowadays - fields and tasks. Knowledge representation. What is knowledge? Elements of knowledge: objects, features, relations, classes, facts and rules. Proce-dural vs. declarative representation of knowledge. Methods: decision tables, semantic networks, frames, scripts, predicates, rules. Examples. Conditions of complete and sound knowledge description - examples.


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Reasoning Methods. Mathematical logic as a ground for reasoning. Concepts of truth, a fact, an evidence, and a problem. Different ap-proaches to reasoning in AI: Induction: learning as an example of induction. Tools of induction e.g. generalization, replacement of values by variables. Traps of analogies. The role of generalization in knowledge gathering. Examples of EURISKO inductive reasoning. Deduction vs. abduction: choice between efficiency and human-like reasoning. Modus ponens. Reasoning with certainty measures. Probabilistic reasoning: Condi-tional probability and Bayes’ formula. Propagation of conditional probability in Pearl’s networks. Difference between belief measure and probability. Dempster-Shafer theory of evidence based on basic probability assignment. Differences between basic probability as-signment and probability distribution. Fuzzy reasoning: Fuzzy set. Generalized modus ponens. Fuzzy rules Expert systems. Definition and tasks. Various structures with applica-tions: semantic networks (TOXOPERT, CASNET), frames (CENTAUR), rules (MYCIN). Inference in expert systems: forward chaining and backward chaining. What is bi-directional reasoning ? Certainty measures in expert system reasoning: probability (ILIAD), certainty factor (MYCIN), fuzzy sets (CADIAG). Various solutions of the same diagnostic problems: Hepar and Hepaexpert. AI computer languages. Basics of PROLOG and LISP standards. Understanding of lists, backward chaining and recursive rules. Alge-braic operations. Natural language processing. Syntactic and semantic analysis. A syntactic analysis of a sentence - top-down and bottom-up parsing. Chatbots – ELIZA and ALICE systems of dialogs. Context-free grammars and analysis of signals. Augmented Transition Networks - examples, the use of ATN to a computer dialog and a translation of languages. Some procedures used in ATN. An analysis of natural language in medicine. SNOMED and ICD-9 - codes and thesauri. System WAREL for data search. Fuzzy sets in identification and Control. Norms and conorms. Op-erations on fuzzy sets. Sugeno-Takagi rules and identification. Mam-dani-like control.


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Clustering. ISODATA and FUZZY ISODATA algorithms with ex-amples. Neural networks. Development of neural networks (NN), their theory and applications during the last decade. Nonlinear nature of a neuron (basic building block of NN) as a ground for many scientific problems solving. Examples of NN application in: system identification, adap-tive filtering and blind adaptation. The model of perceptron and its development to artificial retina implant. Genetic algorithms. Genetic operators: reproduction, crossover muta-tion. Fitness (objective) function. Binary vs. floating point coding. Fields of applications. Comparison with other evolutionary methods (evolutionary programming, evolution strategies.



M1.17.1 Computer networks I 5 30 30 6 Lecturer: Jerzy Mo�ci�ski Objectives of the course

Overall objectives of the course include providing students with basic as well as advanced knowledge concerning components of computer network: communication part, server computers, client computers, modems. Types of services offered by computer network servers are covered in detail as part of the course. Internet services, Internet and TCP/IP protocol suite, TCP/IP protocol structure, physical, data, net-work, transport and application layers tasks in computer network are also considered. Course description

The course on Computer Networks concerns the following groups of topics from the computer networks field: Introduction, computer networks keywords, requirements concerning structure and operation of computer networks and multi-user computer


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systems. Computer network user, user in multi-user computer system, network servers, multi-user systems servers. Computer networks types. Concepts of Local Area Network (LAN) and Wide Area Network (WAN). Internet and TCP/IP protocol suite. Basic components of computer network: communication part, server computers, client computers, modems. Packets and frames. Types of services offered by computer network servers. Internet ser-vices. Internet network protocol, TCP/IP. TCP/IP protocol structure, physical, data, network, transport and application layers tasks in com-puter network. TCP/IP protocol suite in detail, IP v IPv6 Nodes nam-ing concepts in Internet network. Computer network applications. Concepts and rules concerning re-mote usage of computer systems (remote login). Transferring data between computer systems (file transfer protocol). Concepts and rules concerning e-mail usage. Internet technologies, HTTP protocol and www systems architecture, HTML language, CSS concept, JavaScript technology, XML and MathML, Flash technology basics. Object oriented programming concepts in Java, Java and internet ser-vices programming, applications, applets and servlets, JSP. CGI, ASP, JSP and PHP technologies, Internet database systems, simple MySQL and PostgreSQL based systems configuration. Internet technologies and e-learning systems, open and distance-learning concepts, tele-laboratories and virtual laboratories solutions for enhancing university laboratories access. Introduction to UNIX operating system. Basic file and directory op-eration in UNIX system. Resource access rights in multi-user com-puter systems. Basic file processing commands in UNIX system. Network concepts in UNIX operating system. Rules concerning remote usage of file system resources in computer network. Remote access to workstation in network operating system. Gathering information concerning configuration and status of net-worked computer system. Information and data transfer between users in multi-user computer system. Changing access rights to files in multi-user operating system. Files and data security. Programming in the UNIX system shell language. Novell NetWare system – concept, planning the structure, network directory services (NDS), filesystem structure.


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Internet services for engineering education.



M1.18.1 Microprocessor systems I 5 30 15 4 M1.18.2 Microprocessor systems II 6 15 30 5

M1.18.3 Microprocessor systems III - project 7 15 2

Lecturer: Bartłomiej Zieli�ski, Adam Milik Course description

Microcomputer and microprocessor. Principles of von Neumann architecture. Arithmetical-logical unit. Accumulator, flags. Machine and command cycle. Addressing modes. Data exchange between the microprocessor and its environment: polling, interrupts, DMA. De-vices addressing; separate I/O and memory-mapped I/O. Serial (syn-chronous and asynchronous) and parallel transmission. Single-chip microcomputer 8051. Pins, basic machine cycles. Inter-nal RAM. Special registers. ALU, flags. I/O ports. Buffering. Timer-counter unit. Single-chip microcomputer 8051. Serial port. Multiprocessor com-munication. Interrupts. Reset, low-power modes. Expanding the cen-tral unit: external program and data memories, I/O circuits, additional interrupts. Parallel I/O. How to simply organise a parallel transmission with acknowledgement. Universal register 8212. Programmable circuit 8255; structure, operation modes, registers, programming, applica-tions. Advanced functions of parallel I/O devices (selected properties of Z-80 PIO). Serial transmission circuits and timer-counters. Serial transmission circuit 8251; structure, operation modes, registers, programming. Timer-counter unit 8253; structure, operation modes, registers, pro-gramming.


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Interrupt controllers 8214, 8259 and 8259A; structure, operation modes, registers. Examples of daisy-chain and cascade connections. Cooperation with 8-bit and 16-bit microprocessors. DMA controllers 8257, 8237. Structure, operating modes, registers, programming. Advanced functions of DMA controllers (selected properties of Z-80 DMA). 8051 microprocessor programming. Command list, commands groups, programming techniques examples. Modern microcontrollers. Harvard architecture - properties, advan-tages and disadvantages. PIC family microcontrollers - data and pro-gram memory organisation, addressing modes, interrrupt controller. AVR family microcontrollers - data and program memory organisa-tion, addressing modes, interrrupt controller. 8086 microprocessor. Structure; EU and BIU blocks. Registers, seg-mented memory organisation. Logical and physical addresses. Pins. Minimal and maximal operation modes. Memory organisation. Inter-rupts. Floating point coprocessor 8087. Co-operation with 8086. Data ty-pes. Internal registers. Microcomputers IBM PC/XT and PC/AT. Structure. ISA 8- and 16-bit buses. Microprocessor evolution from 8086 to 80486. Microprocessor 80286; new properties, virtual mode addressing, co-operation with 80287 coprocessor. Microprocessor 80386; new properties, virtual mode addressing, co-operation with 80287 or 80387 coprocessors. 80486 Microprocessor; architecture. Signals. Registers and flags. Logical and physical addresses. Segmentation; segment descriptors, descriptor registers. Paging; page directory structure, directory ele-ments, TLB buffers. 80486 Microprocessor. Cache memory. Serial transfers. Write buff-ers. Task protection. Task state segment. System segments and gates descriptors. Interrupts and exceptions. Interrupt table in real and vir-tual mode. IBM PC Microcomputer; architecture development. EISA, MCA, VLB buses; basic properties. PCI bus. Structure of PCI bus equipped computer. PCI signals and cycles. Interrupts in PCI system


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PCI bus; configuration memory. Access to the configuration memory in IBM PC. Device classification. AGP bus; computer structure, sig-nals, operation modes. Improving microprocessor efficiency. Pipelining. Superscalar mi-croprocessor. Command dependencies solving. Branch prediction. BTB table, static and dynamic methods. Code optimisation. Cache; connection to the microprocessor, organisation. MESI protocol. Pentium and Pentium MMX microprocessors. Structure. Pipelin-ing, instruction pairing. Cache. Pipelined FPU. MMX commands and data types. Pentium Pro, Pentium II, Pentium III microprocessors. Structure. RISC kernel operation. Instruction decoding. Reorder Buffer, Reser-vation Station, Memory Reorder Buffer. Execution units. L1 and L2 cache. Command list enhancements and new data types; SSE, 3Dnow. Microprocessor identification. Modern memories. DRAM (SDRAM), DDRAM, RAMBUS Modern microprocessors. Intel Pentium 4, AMD Athlon. 64-bit ar-chitectures: VLIW, EPIC. Intel Itanium and AMD Hammer - a short comparison.



M1.19 Signal processing and communication 5 30 30 5

Lecturer: Katarzyna Mo�ci�ska


The main goal of the course is to give students the basic knowledge concerning signal processing. The course can be regarded as founda-tion to more specialized courses like digital signal processing, analog circuit design and others.


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Course description

The course on Signal Processing and Communication covers the fol-lowing topics: Introduction to signal processing: definition of signal. Signal proper-ties. Some special signals of interest. Periodic signals: orthogonality. Parseval’s theorem. Trigonometric Fourier series. Periodic signals in linear, shift invariant systems. Equivalent forms of Fourier series. Discrete spectrum. Frequency representation of aperiodic signals. Power and energy sig-nals. Fourier transform: definition, properties. Signal modulation: amplitude and frequency modulation – basic terms, description in time and frequency domain. Bandwidth and effi-ciency. Realization of modulation/demodulation. Ideal and realizable filters. Relation of frequency characteristic to im-pulse response. Realizable filters. Introduction to analog filter design. Butterworth lowpass filter. Frequency transformations. Sampling and its implication: ideal sampling in the time and fre-quency domain. Shannon’s theorem. Aliasing. Discrete –time description of signals and systems: basic sequences, linear – time invariant systems, convolution, causality criterion. Fourier transform of discrete – time signals: definition, properties, use in signal processing. Z transform: definition, region of convergence, properties. System function of a digital filter. Representation of a digital circuit: difference equation, block diagram, system function, pole – zero pattern. DFT and FFT. Definition and properties of DFT. Linear vs circular convolution. Linear convolution with DFT. FFT decimation-in-time algorithm. (Option) Advanced topics: Time – frequency representation. Uncer-tainity principle. Short time Fourier transform. Wavelet transform.



M1.20 Computer graphics and vi-sion I 6 30 30 5


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Lecturer: Konrad Wojciechowski Course description

3-D and M-D Geometry in Computer Graphics and Computer Vision. Affine transformations. Changing coordinate systems. Nonlinear transforms. Versors and tensors. Color and Color Spaces. Sampling Theory. Fourier approach. Aliasing. Prefiltering. Stochastic sampling. Representation of Objects. Polygonal representation. Bicubic paramet-ric patch nets. Constructive solid geometry. Space subdivision tech-niques. Parametric representation of 3D solids and curves. B-spline. Approximation to a surface patch using polygon mesh. NURBS and beta-splines. Modeling objects with bicubic parametric nets. Viewing Systems. Reflection and Illumination Models. The Phong reflection model. LUT with reflection model. Empirical transparency. The Cook and Torrance model. Illumination source models. Rendering Algo-rithms. Culling and clipping. Incremental shading techniques. Rasteri-zation. Hidden surface removal. Volume rendering algorithms. Paral-lel versus perspective projection. Lighting model. Shadows and Tex-tures. Shadows and their function. Shadow algorithms. Texture and their models. 2D and 3D texture. Ray Tracing. Basic algorithm. Re-cursive implementation of ray tracing. Reflection-illumination model. Shadows. Distributed ray tracing. Making ray tracing efficient. Radi-osity. Radiosity theory. Development of the radiosity method. Hybrid radiosity and ray tracing. 3D Computer Animation. Keyframing sys-tems. Explicit motion specifications-trajectory approach. Image Rep-resentations. Continuous argument. Fourier transform. Laplace trans-form. PDE. Discrete argument. Z-transform. 2-D and M-D discrete system. Continuous image stochastic representation. Discrete image stochastic representation. Image sampling and reconstruction. Scalar and vector quantization. Discrete 2-D Linear Processing. Superposi-tion and convolution. 2D Unitary Transforms. Fourier transform. Co-sine and sine transform. Hadamard and Haar transform. Wavelet transform. Karhunen-Loeve transform. M-D unitary transforms. Dis-crete 2-D and 3-D Nonlinear Processing. Ordering statistics. Mof-phological image processing. Hit or miss transformations. Dilatation, erosion, opening closing. Gray scale image morphological operations. Image Improvement. Enhancement. Noise cleaning. Edge crispening.


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Color and multispectral image enhancement. Geometrical Image Modification. Translation, zooming, rotation. Spatial warping. Per-spective transformation. Image Analysis. Image segmentation. Shape analysis. Image feature extraction. Pattern recognition. Classification. Scene Reconstruction. Point to point, lines and regions correspon-dence. Stereovision and active vision.



M1.21.1 Data bases I 6 30 30 6 M1.21.2 Data bases II 7 30 30 6 Lecturer: Paweł Kasprowski Objectives of the course

The purpose of the subject is to teach students how to develop and use modern database systems. Course description

Usage of databases – functions and architecture of Database Manage-ment System (DBMS). Models of databases – network, hierarchical and relational models. Relational algebra – selections, projections, joins. Structured Query Language (SQL) - Data Definition Language (DDL), Data Manipulation Language (DML), Data Query Language (DQL). Searching in relational database using SELECT phrase. Advanced searching - grouping data, aggregations, views, outer joins, nested queries, correlations. Preserving database referential integrity - primary and foreign keys. Security in databases - users, roles, rights. Developing databases – functional dependencies, normal forms, ERD diagrams. Concurrent access to databases – locks, transactions, isolation levels. Programming in databases – stored procedures, functions, triggers.


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Architectures of modern database systems – client-server and 3-trier architectures.



M1.22 Electromechanical devices 6 30 15 4 Lecturer: Krzysztof Kluszczy�ski Course description

Properties of materials: B-H curves, hysteresis , soft and hard mag-netic materials, permanent magnets, hysteresis and eddy current losses. Lamination of magnetic cores. Concentrated winding: inductor. Magnetically coupled circuits. Single and three-phase transformer: construction, theory and performance. Equivalent circuits. Steady-state and transient operation. Basics of electromechanical energy conversion: force and torque de-velopment. General aspects of motor selection for electrical drives. Alternating Current (AC) machines. Distributed windings and mag-netic fields of AC machines. Winding, pitch and breadth factors. Con-verters for AC drive systems. Asynchronous machines: construction, theory and performance. Basic types of induction motors. Equivalent circuits of slip-ring and squirrel cage motors. Steady-state and transient operation. Speed-torque char-acteristics. Starting methods. Performance of converter-fed induction motors. Speed control: U/f and vector control schemes. Synchronous machines: construction, theory and performance. Basic types of synchronous machines. Generator and motor operation of salient-pole and cylindrical-rotor machines. Equivalent circuits. Steady-state and transient operation. Load angle-torque characteris-tics. Methods of starting and synchronisation. Stability margin. Per-formance of converter-fed synchronous machine. Control schemes for rotor positioning. Direct Current (DC) machines: windings and commutation. Basic types of DC machines: generator and motor operation. Equivalent


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circuits of series, shunt and separately excited machines. Steady-state and transient operation. Starting methods. Solid-state converters for DC drive systems and speed control. DC servomotors. Application and control schemes of small electric motors. Single-phase induction motors. Stepping motors. Switched Reluctance Mo-tors (SRM). Permanent Magnet motors. Hysteresis motors.



M1.24.1 Operating systems I 6 30 30 6 M1.24.2 Operating systems II 7 30 30 5 Lecturer: Grzegorz Hry� Course description

The main goal of the Operating Systems course is to make the stu-dents familiar with the general concepts of an operating system acting as a basic piece of software in every computer system. Basic functions and supported services are described. The first part of the course - which is obligatory for all students - comprises the theoretical aspects of an operating system related problems, like: the idea of a process, a thread, process queue, mutual process communication and synchroni-sation, memory management issues, virtual memory mechanisms, input-output operation handling, data management, file systems and data mass storage systems management. The laboratories are focused on basic elements of a workstation operating system maintenance (Windows XP and Linux used as the examples), starting with its in-stallation and everyday routines, following with monitoring, system tuning and ending with general troubleshooting issues. The second part of the course - which is obligatory only for those, who choose the Computer Science specialisation - aims at presenting the network related topics. This part describes the distributed file sys-tems, the directory services, public key infrastructure related topics, some network services (like DNS, DHCP) and the remote access methods. The laboratories reflect the lectures, although the students'


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attention is focused on the configuration of the server side of the above mentioned services (Windows 2003 and Linux are used as the examples).

Postgraduate courses: Information Processing for Control



M2.1 Adaptive systems in control 7 30 15 4 Lecturer: Jerzy Mo�ci�ski Objectives of the course

The main objective of the course is to provide the students with basic and advanced knowledge concerning theory, analysis and synthesis of adaptive control systems. During the course the students should de-velop the skills concerning the methods of theoretical analysis and synthesis of adaptive control systems as well as the skills of building and using computer simulation packages for analysing the behaviour of such complicated control systems. Course description

Controllers tuning task. Classification of adaptive control systems. Model reference adaptive control systems. Gain scheduling simple and advanced adaptive control schemes. Adaptive control systems with model identification. Open loop unstable and non-minimumphase plants in adaptive control. Basic plant and controller models. De-mands concerning adaptive control systems stability, convergence and robustness. Direct and indirect adaptive control systems. Transfer function plant model and prediction plant model . Identification in adaptive control systems, transfer function and prediction model iden-tification. Stochastic disturbances as disturbance model in control systems. De-terministic disturbances: description, deterministic disturbances types, attenuating deterministic disturbances. Simulation experiments’ role in analysis and synthesis of adaptive control systems. Performance assessment in adaptive control systems. Adaptive control with pole/zero placement. Choice of poles and zeros for desired control system characteristics. Model reference adaptive control systems. Adaptive minimum variance control. Choice of con-trol weighting scheme and parameters for minimum variance control-lers. Adaptive long range predictive controllers. Predictive controllers


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based on parametric and nonparametric plant models, GPC control algorithm. Recursive estimation algorithms as used in adaptive control systems. Forgetting factor and its role with respect to identification methods properties. Improving numerical properties of recursive esti-mation methods. Stability of adaptive control systems, convergence of parameters estimates in recursive estimation algorithms. Continuous time plant model adaptive control systems. Fuzzy logic methods for design and synthesis of control systems, fuzzy controllers design, features and application examples. Evolutionary optimisation techniques in identification and model structure choice for adaptive control systems. Multidimensional control systems with adaptation, multi input / multi output plants models, estimation techniques for multidimensional models. Autotuning, adaptive PID controllers. Adaptive filtering, filters with adaptation properties, control and tele-communications application.



M2.2 CAD of control systems 7 30 30 project 5

Lecturer: Marian Błachuta


The subject aims at making students familiar with elements of CADCS, in particular with numerical methods used in computational algorithms for control systems, as well as with typical procedures and software packages Course description

Historical outline. Overview of software packages. MATLAB system and toolboxes related with control, signal processing and system iden-tification. Selected issues of linear algebra: norms of vectors and ma-


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trices, orthogonal and unitary matrices, Schur form. Numerical algo-rithms of linear algebra used in numerical algorithms for control sys-tems: problem conditioning and numerical stability, systems of linear equations, Hausholder transformation and QR factorization, transfor-mation to Hessenberg and Schur forms, generalized eigenvalues and QZ algorithm. Singular Value Decomposition and its applications. Matrix exponential and matrix logarithm. Survey of selected proce-dures from CONTROL SYSTEMS TOOLBOX. Relationships be-tween state-space and transfer function descriptions, canonical repre-sentations, poles and zeros. Sampled data systems: conversion be-tween continuous-time and discrete-time descriptions, delta operator approach. Controllability, observability, determining controllable and observable part, observability and controllability grammians, balanced realizations, system order reduction. Design methods for SISO con-trol systems. Mathematical models for MIMO systems: state-space, matrix transfer function, matrix fraction description. Smith-McMillan form of transfer function matrix, poles and zeros, relationships be-tween description forms. Principal gains and characteristic loci. De-sign of decentralized controllers. The characteristic locus method. Approximate commutative controllers.



M2.3 Computer controlled sys-tems 7 30 15 4

Lecturer: Ryszard Jakuszewski


This course is designed primarily for students wanting to create ad-vanced control and process monitoring systems. The students should obtain knowledge of theoretical fundamentals and of practical meth-ods used in modern SCADA systems and industrial automation soft-ware.


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Course description

The world’s leading industrial automation software solutions, provid-ing process visualization, data acquisition and supervisory control of plant floor operations are discussed and trained during laboratory classes. This solutions give students the power to precisely monitor and control every aspect of manufacturing industry processes, as well as equipment and resources, resulting in faster response to production issues, less waste, improved quality, faster time-to-market with new products and increased profitability. The specialists who have ac-quired skills in SCADA systems are looked for in job market all over the world. The course teaches basic SCADA and HMI topics like Process Data-base blocks, driver configuration, graphic design, data archiving, re-porting, alarm strategies and security. The course is intended to provide the student a base level of profi-ciency using some of the American software solutions and also dis-cusses more advanced features. VBA scripting is covered primarily as a tool for automating tasks for the operator. The student will also be-come familiar with some of the tools and concepts available for opti-mizing and troubleshooting such software. Basic topics: Basics of Graphics; I/O Driver Configuration; Alarming; Trending; System Configuration; Process Database Development; Scripting; Optimization; Torubleshooting; Security; Reporting More advanced topics: System Architecture; Using OPC; Understanding Database Dynamos; Optimizing the Process Database; Introduction to ODBC; Sending Alarms to ODBC; Introduction to SQL; Using SQL Database Tags; Using ActiveX; VisiconX; Reporting; View Auto-Failover; LAN Re-dundancy; System Optimization


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M2.4 Hierarchical control 7 30 30 5 Lecturer: Krzysztof Fujarewicz


This course is addressed to students interested in systems analysis, control engineering, management and decision making. It covers basic methods used in solving control and optimization problems associated with large-scale and complex systems. After completing the course student has basic knowledge in optimization and control of large scale systems. This knowledge consists of methods of analysis of composite systems, solving structured optimization problems and designing hier-archical and decentralized feedback systems.

Course description

Introduction and the terminology. Large scale systems, complex sys-tems, decomposition coordination. Different types of hierarchical structures: multilayer structure and multilevel structure. Mathematical models of systems. Static models. Mathematical model of the plan-ning problem for the oil refinery. Dynamical models. Concentrated-parameter models and distributed-parameter models. Stirred-tank con-tinuous-flow reactor. Types of variables in hierarchical structures: state variables, manipulated and input variables. Constraints. Descrip-tion of complex systems, subsystems, the structure matrix. Static char-acteristics.

Multilayer systems. Decomposition. Stabilization layer and its struc-ture: output and control variables, assignment of variables. Multilayer structure of control and optimization for continuous-flow reactor.

Multilevel optimization systems. Simplex method. Decomposition of linear programming problems, Dantzig-Wolf method. Decomposition and coordination in nonlinear static optimization problems. Direct method of coordination. Induced constraints. Direct method with


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penalty function. The price method. Dynamic programming. Mixed methods.

Identification and optimization of nonlinear dynamical systems. Sensi-tivity analysis. Gradient derivation. Adjoint systems. Gradient calcula-tion with the adjoint system. Neural models. Hybrid models. Gradient-based identification and optimization of complex nonlinear systems.



M2.5 Robot vision 7 30 30 6 Lecturer: Henryk Palus

Course description

Sensory systems for advanced robots. Human vision system. Com-parison of human and robot vision. Vision sensors (CCD line sensors and area sensors). Parameters of colour cameras. Lighting systems. Optical systems (lenses for cameras, filters). Frame grabbers, image processors and computers. A/D conversion and fundamentals of video. Binary images. Digital image processing operators. Elements of mathematical morphology. Image segmentation techniques. Region properties: shape factors and Euler number. Region properties: geo-metrical moments. Colour representations and colour sensors. Colour image processing. Knowledge representation methods. Knowledge-based vision systems. Applications of robot vision systems.


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M2.6 Robotics 7 30 30 6 Lecturer: Aleksander Staszulonek


The goal of this course is presentation of the main elements of robot theory: mathematics, programming and control. Course description

Program of the course includes: homogenous transformations, deriva-tion of kinematic equations, kinematic equations solution, dynamics, control, trajectory execution and programming. Section dedicated to homogenous transformations contains description of basic definitions like vectors, planes, coordinate frames, basic transformations, relative and inverse transformations, equivalent angle and axis of rotation. Section dedicated to derivation of kinematic equations deals with different coordinate systems, specification of A matrices for manipulator’s prismatic and rotational links, specification of T matrices in terms of A matrices. As the example, kinematic equa-tions of Stanford and Elbow Manipulators are derived. Methods lead-ing to the solution of kinematic equations are described and solutions for Stanford and Elbow manipulators are presented. The dynamics of robot manipulators is then presented using Lagrangian equations. Re-quirements imposed on robot control systems are presented and set point and tracking control problems defined. Basic theory and meth-odology of robot control is presented on the examples of most fre-quently applied control structures. PID and sliding mode controllers are discussed.


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Course load


ECTS

M2.7 Advanced control 8 45 30 15 7 Lecturer: Ryszard Gessing


Nonlinear control systems, being a subject of the course, need for their analysis and design advanced computer tools. This is related with the fact that, though the nonlinear systems are significantly richer in phe-nomena, the methods of their analysis and design are significantly weaker than those of linear systems. Effective usage of computer tools is possible only then when one has an appropriate knowledge of ad-vanced nonlinear control. Therefore in the course a big effort is made to give a good foundation of nonlinear control knowledge. This is the main objective of the course. Course description

Nonlinear systems. Models of nonlinear systems - nonlinear differen-tial equations. Characteristics of nonlinear elements. Nonlinearities, their description and characteristics. Examples of nonlinear elements. Phase plane analysis. Equations of phase trajectories, phase portrait. Derivation of phase trajectories: - method of isoclines; - solution of phase trajectory equation. Properties of phase trajectories. Singular points and trajectories. Method of describing function. Definition of describing function - comparison with frequency response. Examples of describing func-tions. Condition of free oscillations. Determination of oscillation pa-rameters. Application to stability analysis of control systems. Indirect and direct Lyapunov methods. Lyapunov definition of stabil-ity and asymptotic stability. Local stability, indirect Lyapunov method. Determination of equilibrium points. Global stability, direct Lyapunov method. Determination of stability region (domain of at-traction).


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Analysis of discrete-time systems. The case when nonlinearity appears - in continuous-time part of the system; - in discrete-time part of the system. Difference equations - determination of waveforms. Influence of nonlinearities on control quality, antiwindup solutions: analog, digital Control systems with dead zone relay. Voltage stabilization system and its phase plane analysis, determination of stability condition. Sys-tem stabilization. Influence of delay. On-off relay control. System description - relation between switching frequency and oscillation magnitude. Influence of parameters on con-trol waveforms. Decrease of oscillation magnitude. Sliding - mode control. Description of sliding mode control, sliding surface, chattering effect. Design of sliding mode control law. Exam-ple and results of simulations. Extremal control. Systems with plants having extremum. System with derivative sign examination. System with outside modulating signal, synchronic detection, approximate system description. The case of plant with multiple inputs. Adaptive control. Systems with gain scheduling. Model reference adaptive systems. Systems with current identification. Autotuning regulators. Optimal control. Maximum principle. Time-optimal control. Example of design.



M2.8 Computer integrated manu-facturing 8 30 15 5

Lecturer: Waldemar Grzechca

Course description

The subject Computer Integrated Manufacturing is an introduction into scheduling problems in manufacturing systems. It contains of two


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parts. In the first part ideas of single machine scheduling, parallel ma-chines scheduling, flow shop and job shop problems are solved. Part two contains philosophy of modern manufacturing systems. Introduction – philosophy of scheduling in computer and manufactur-ing systems, basic terms, complexity of scheduling problems Single machine – minimizing schedule length, mean flow time, due date criteria Parallel machines – heuristic methods, minimizing schedule length, mean flow time, due date criteria Branch and Bound Algorithm – optimization of minimum sum of lateness Job shop – basic ideas, LIFO, FIFO, EDD, LWR, SPT, LPT methods Flow shop – Johnson’s algorithm for two machines and Johnson’s rule for N machines SALBP – simple assembly line balancing problem, description of problem, different lines SALBP – finding solutions, exact methods SALBP – finding solutions, heuristic methods Genetic algorithms – basic ideas, description of parameters Genetic algorithms in practice – finding solutions of scheduling prob-lems, assembly line balancing problem CIM – model Y of Computer Integrated Manufacturing Philosophy of MRP, MRP II and ERP Just in Time methods – benefits and difficulties TOC – Goldratt’s philosophy of production systems Lean Manufacturing – ideas and solutions



M2.9.1 Programmable controllers I 8 30 30 6

M2.9.2 Programmable controllers II - project 9 30 3


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Lecturer: Jerzy Kasprzyk


The main goal is to present ways of using and programming Pro-grammable Logic Controllers (PLC) in automation and control. Course description

PLC – introduction, basic ideas, ways of working and programming, some examples of AC motor control. International Standard IEC 61131 – parts of the standard, software model, communication model, elements of programming languages. Literals, data types (elementary and derived), variable declaration. Program organization units - functions, function blocks, programs. Standard functions and function blocks. Graphical programming languages - Ladder Diagram (LD), Function Block Diagram (FBD). Textual programming languages – Instruction List (IL), Structure Text (ST). Structuring the program using Sequential Function Chart (SFC). PID control in PLC. Configuration elements – configurations, resources, tasks, access paths, tasks execution. PLC hardware – modules, central processing unit (CPU), digital in-put/output modules, analog I/O modules. Redundancy in PLC systems. Communication in PLC systems and with SCADA systems. Man-Machine Interface (MMI, HMI). Application of PLCs in automation and control.



M2.10 Quality control 8 30 15 3


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Lecturers: Marek Kimmel, Adam Czornik


Use of statistical methods for improvement of quality in industrial setting (Statistical Process Control). Application of computer package QMC to analysis of simulated and real-life data. Application of sto-chastic control theory to design fault-prone systems. Course description

Departing from the Deming paradigm, the stepwise method of quality improvement, using a statistical approach, is developed. It leads logi-cally to application of various types of run charts, for monitoring processes with different statistical properties. The run charts vary from simplest acceptance-rejection charts to sophisticated sequential ap-proaches. Subsequently, attention will be shifted towards decomposi-tion of the process and design of experiments. Weekly assignments will generally require the use of a computer package, either of spread-sheet type (like MS Excel) or the specialized QMC package (will be provided). In some assignments, students will test new procedures developed for the QMC package. Emphasis will be divided between sound theoretical principles (using simple probabilistic techniques) and computational techniques, using simulated and real-life data. One way to design control systems robust in the sense of possible failure is to use piecewise deterministic processes with Markov jumps in pa-rameters. The state of such systems is hybrid : to standard continuous process state variables one should append discrete variables called mode which are described by Markov chains. For linear systems it is possible to built complete design methodology. List of major topics Statistical process control: A brief overview, Deming’s paradigm, Pareto principle Acceptance-rejection and mean and standard deviation control charts Sequential approaches (CUSUM charts) Exploratory methods and simplex algorithm of optimization Experimental designs Multivariate approaches


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Linear systems with Markov jumps JLQ problem



M2.11 Reliability and intrinisic safety 8 15 15 3

Lecturer: Jerzy Fr�czek


To acquaint the students with: 1). A necessity of reliability assessment of technical objects and systems in which reliability structures, main-tenance and a human role are taken into account; 2). Constructions of explosion-proof apparatus and designing of measurement and auto-matic control systems with intelligent transducers, as an intrinsically safe systems, in which the reliability plays the most important role. Course description

Definition of a reliability of a technical object in the context of meas-urable and nonmeasurable characteristics in the defined environmental conditions. Basic functions and reliability characteristics. Reliability block diagrams of systems (static and dynamic). Reliability models of objects and systems. An estimation of reliability characteristics of objects and systems. Statistical methods in the reliability assessment (including ” fuzzy reliability”). A model of a “critical human error”. An influence of the maintenance on the reliability. An inspection in-terval and its influence on the reliability. Definition of an explosion-proof of apparatus and systems. A role of the reliability in different types of explosion-proof protections. An intrinsically safe protection as the most safe protection of measure-ment and automatic control systems. Requirements in relation to ele-ments of circuits and systems containing of: an equipment located in a dangerous area, in a safe area and a connecting cables. Classifications


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of: gases, vapour, dusts, locations, apparatus. National and interna-tional standards. Certification procedures. Marking. Certificates and their mutual recognition in different countries.



M2.12 Sensors and actuators 8 45 30 6 Lecturer: Dariusz Buchczik


To show the technology, the construction, the theory of operation and the applications of modern integrated solid–state sensors and actua-tors. There are also presented new trends in sensor technology and integration into the network-enabled smart transducers. Course description

Introduction: scope of lectures, literature. Examples of integrated sen-sors and actuators (micropumps, microvalves, micromachines). Mi-croelectromechanical systems (MEMS, MEOMS, µTAS, VSM). Inte-grated sensors technology, application areas. Silicon and its properties. MEMS technologies: bulk micromachining, surface micromachiming, LIGA, wafer bonding, laser micromachin-ing, 3-D stereo lithography. Actuators. Principles of actuation: electrostatic, electromagnetic, pie-zoelectric, thermal, electromagnetic. Examples of actuators. Temperature sensors and its electronic circuits. Thermoresistive sen-sors (resistance temperature detectors, silicon resistive sensors, ther-mistors), semiconductor pn-junction sensors, thermoelectric contact sensors (thermocouples). Pressure sensors: basic definitions, units of pressure and conversion. Sensing elements: diaphragms, bellows, tubes. Detection methods: capacitive, piezoresistive, resonant, piezoelectric.


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Acceleration sensors: dynamic model of accelerometer, damping and frequency response, cross-axis sensitivity, self testing, force feedback, multiaxial accelerometers. Principles of operation – piezoelectric, pie-zoresistive and capacitive. Force sensors: basic types of sensors: piezoresistive, capacitive, reso-nant, piezoelectric. Tactile sensors: force sensitive resistors, piezoelec-tric tactile sensors. Humidity sensors: basic concepts and definitions, impedance sensors (resistive and capacitive), chilled mirror sensors – methods of conden-sation detection. Fibre optics sensors: basic concepts, optical fibres. Multimode sensors with internal and external amplitude modulation, sensors utilizing se-lective wavelength modulation. Monomode sensors: interferometers and their fibre optics realisation, polarometric sensors.



M2.13 Applied digital signal proc-essing 9 30 15 3

Lecturer: Marek Pawełczyk


The aim of this lecture is to present issues in modern signal processing techniques with focus on applications. It constitutes a pedagogical compilation of fundamentals, algorithm forms, behavioural insights, and application guidelines. The intertwining of theory and practice is demonstrated by numerous examples and verified during laboratories. Course description

Digital Signal Processing (DSP) is distinguished from other areas of computer science by the unique type of data it uses: signals. In the era of rapid development of microprocessors it gains significant interest and finds applications in many fields of everyday life. DSP plays an


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increasingly central role in the development of telecommunications and information processing systems, and has a wide range of applica-tions in multimedia technology, audio-visual systems, cellular mobile communications, adaptive network management, radar and ultrasonic systems, pattern analysis, medical signal processing, financial data forecasting, decision making, etc. The course touches following subjects: The breadth and depth of DSP; Fourier transforms; Sampling, analogue-to-digital and digital-to-analogue conversion, quantization; Correlation analysis; Signal win-dowing; Spectral analysis; Interpolation and decimation; Conversion of sampling frequency and multi-rate signal processing; Spectral sub-traction; Digital filters design; Wiener filter; Kalman filter; Signal analysis and forecasting; Wavelet transform; Adaptive control: mini-mum-variance control, predictive control, zeros/poles placement, model reference adaptive systems, and adaptive Wiener filters; Active control of acoustic noise; Echo generation and cancellation; Speech processing and recognition; Distance detection; Digital Signal Proces-sors.



M2.14 Biotechnical systems 9 30 15 3 Lecturers: Marek Kimmel, Witold Noco�


The objective of the course is to provide an overview of selected tech-nologies and analytic tools involved in modern biotechnology and bioinformatics. Course description

The course consists of several modules: Measurement of Gene Expression Using DNA Microarrays


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Background: The dogma of molecular biology concerning information flow in cells. Gene expression as a descriptor of cell's state. DNA-microarray and related technologies: oligonuleotide chips, Affymetrix chips, nylon membranes, SAGE (sequential analysis of gene expres-sion). Examples of medical and biological applications: cancer diag-nostics, time patterns of gene expression. Analysis of gene expression data: Clustering, self-organizing maps, support vector machines, analysis of variance. Gene networks. Modeling and Estimation of Signaling Pathways in Biological Cells Examples illustrating importance of signaling pathways: Antiviral defense using interferon signaling, Wnt regulation and genesis of co-lon cancer, p53 signaling and DNA repair. Mechanisms of gene tran-scription, polymerase, transcription factors, binding motifs. Signal transduction: cell surface receptors, kinase cascades. Modeling of sig-naling pathways: Deterministic models using ordinary differential equations, stochastic models using markov processes. Spatial effects. Signaling pathway as a control system, estimation of parameters and analysis of stability. The main objective of the second part of the lecture is to provide stu-dents with a basic knowledge and understanding of mechanical, chemical and biological processes involved in wastewater treatment. In particular, the following topics are covered: Basic structure of a wastewater treatment plant, including mechanical and chemical pretreatment, biological part including bioreactors and secondary settlers, sequencing batch reactors. Biology in wastewater treatment: enzymes; catabolic and anabolic processes; organisms in wastewater treatment; nutritional classifica-tion of microorganisms; selection of microorganisms in wastewater treatment; conversions in biological treatment plants. Reactor kinetics of microbial systems: reaction kinetics; reactor hy-draulics; reactor kinetic; matrix representation of the reaction kinetics. Organic carbon removal: fate of soluble components; hydrolysis. Nitrification process; denitrification process; biological phosphorus removal.


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M2.15 Estimation and identifica-tion 9 45 30 6

Lecturers: Zdzisław Duda, Jarosław Figwer


The main goal is to present basics in estimation theory and identifica-tion of static and dynamic linear models. Course description

Estimation theory: Signal Estimation: Linear Estimators, Estimator Design, Estimation based on DiscreteMeasurements, State estimation; Least Squares (LS) Estimation: Least Squares Estimation of Signal Parameters, Recursive form of LS, Weighted Least Squares; Random Discrete-Time Signals and Systems with Random Inputs; Optimal Estimation: Formulating the Problem, Properties of Esti-mates; Maximum Likelihood and Maximum a posteriori Estimation, Mini-mum Mean-Square Error (MMSE) Estimation, The Orthogonality Principle; Linear MMSE Estimation, Orthogonality Principle for LMMSE Es-timation; Comparison of Estimation Methods; Recursive Estimation and the Kalman Filter. Instrumental variable estimation method. Identification Introduction: aims of identification, static and dynamic models, para-metric and non-parametric models, discrete- and continuous-time models, linearity, time-invariance. Static model identification: ordinary least squares (OLS) estimator and its statistic features. Recursive least squares (RLS) estimator and its features.


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Identification of time-varying systems: weighted least squares (WLS), recursive WLS, least mean squares estimator. Non-linear model identification, artificial neural networks. Dynamic model identification: batch OLS, RLS and RWLS and their properties. Algorithms to avoid bias: instrumental variable, recursive prediction error method. Model structure selection and model validation. Experiment design, persistently exciting signals. Identification in a closed-loop – conditions for proper experimenta-tion. Models in frequency domain: power spectral density estimators (pe-riodogram, Blackman-Tuckey method, parametric approach), leakage, time- and frequency-domain windows, frequency response identifica-tion, empirical transfer function estimator.



M2.16 Expert systems 9 30 30 4 Lecturer: Antoni Niederli�ski


To learn designing and testing knowledge bases for the family of rule- and model-based expert system shells rmes. Course description

General information on expert systems. Basic structure. Main proper-ties. Advantages of separating domain knowledge from reasoning. Historical background. The rmes family of rule-and model-based expert system shells. Elementary Exact Expert System Shells (rmes_EE)– Elementary Ex-act Rule Base, Elementary Exact Model Base, Elementary Exact Con-straint Base, Elementary Exact Advice Base, Sound Base, Graphics


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Base. The open world assumption and its consequences. Nesting – its advantages and disadvantages. Basic properties and applications. Elementary exact backward and forward chaining. Testing and diag-nosing elementary exact knowledge bases. Augmented Exact Expert System Shells (rmes_AE)– Augmented Exact Rule Base, Augmented Exact Model Base, Augmented Exact Constraint Base, Augmented Exact Advice Base, Sound Base, Graph-ics Base. The closed world assumption and its consequences. Basic properties and applications. Augmented exact backward and forward chaining. Testing and diagnosing augmented exact knowledge bases. Modeling uncertainty with the help of Stanford Certainty Factor Al-gebra and its extension (cumulative and disjunctive rules). Certainty factors for modeling ignorance, user preferences and fulfillment of relations. How to obtain and verify certainty factors. Elementary Uncertain Expert System Shells (rmes_EU)– Elementary Uncertain Rule Base, Elementary Uncertain Model Base, Elementary Exact Constraint Base, Elementary Uncertain Constraint Base, Uncer-tain Advice Base. Properties and usage. Elementary uncertain back-ward and forward chaining. Testing and diagnosing elementary uncer-tain knowledge bases. Augmented Uncertain Expert System Shells (rmes_AU)– Augmented Uncertain Rule Base, Augmented Uncertain Model Base, Augmented Uncertain Constraint Base, Augmented Exact Constraint Base, Un-certain Advice Base. Properties and usage. Augmented uncertain backward and forward chaining. Testing and diagnosing augmented uncertain knowledge bases.



M2.18 Graphical programming 9 30 15 3 Lecturer: Witold Noco�


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Course description

The main objective of this lecture is to provide the student with a good knowledge and understanding of the graphical programming language LabVIEW (Sometimes referred to as the "G-language"). In detail, on completion of the course, students should be able to: Understand and use all the basic LabVIEW programming structures like: loops, conditional structures and subroutines. Use the data types available in LabVIEW like arrays, clusters, local and global variables. Design virtual instruments for analysis, data storage and presentation of measured variables, signals and other process data (I/O functions). Design simple control systems for real-world processes. Implement the advanced analysis functions using functions available in LabVIEW (FFT for example). Design Internet-ready applications using TCP/IP protocol for commu-nication between different LabVIEW applications. Use dynamical loading of functions in LabVIEW. In addition, introduction will be given to some of the add-ons tool-boxes for LabVIEW, for example: Real-Time programming (using FieldPoint 2010 distributed I/O sys-tem) PID Module. Datalogging and Supervisory Control Module.



M2.19 Modelling and simulation 9 30 30 5 Lecturer: Jacek Czeczot

Course description

The course is dedicated to the modeling and simulation of dynamic and control systems.


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The subject of this course can be divided into two main parts. The first part concentrates on the methodology of deriving nonlinear physical models of lumped systems. This methodology is based on common mass and/or energy conservation laws and it leads to the nonlinear mathematical description of a system in the form of a set of ordinary differential equations. Then, the numerical integration methods for computer simulation of such systems are presented. Both the one-step and multi-step methods are considered and their most important fea-tures (especially their advantages and disadvantages in terms of calcu-lation and implementation complexity) are discussed in details. The second part of the course is dedicated to physical modeling of distrib-uted parameter systems. These systems are generally described by a set of hyperbolic and/or parabolic partial differential equations and the methodology for deriving such models is presented and discussed. For the numerical solving of distributed parameter systems two groups of methods are considered during the course. One group is the DTDS (Discrete Time Discrete Space) group of methods and the second one is the CTDS (Continuous Time Discrete Space) group (so called method of lines). Both groups are presented in details and their calcu-lation and implementation complexity are discussed in details. The lectures are intended only as a theoretical introduction with a very strong practical aspect. However, the theory is discussed and demon-strated rather through examples than through advanced theoretical considerations. Additionally, the laboratory classes follow the lectures and their most important goal is to give the students the opportunity to practice the methods presented during the lectures and to investigate their practical aspects in terms of the application in both real-time simulation and batch simulation. During the laboratory classes, the MATLAB programming language and the LabView programming environment from National Instruments are used.



M2.49 Advanced Image Process-ing 9 15 7 1.5


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Lecturer: Bogdan Smołka


The objective of the course is to make the interested students familiar with the main concepts of digital color image processing. Course description

The course consists of 7 units which cover some of the most important topics in the challenging field of color imaging. Emphasis is placed on applications, as after the course, the students are supposed to be able to utilize the color information in various tasks of computer vi-sion. The course should be of interest for students wishing to extend their knowledge of digital image processing techniques and also for those who are seeking a deeper insight into the digital photography and multimedia. Lecture topics: Human color perception, Color image acquisition methods, Color spaces for computer vision and graphics, Image enhancement techniques, Noise reduction and edge detection in color images, Overview of advanced image compression methods, Color imaging applications: red-eye removal, face detection, cartoons restoration, old photo colorization.

Postgraduate courses: Computer Aided Information Processing



M2.20.1 Analog circuits design I 7 30 30 15 6 M2.20.2 Analog circuits design II 8 30 30 7 Lecturer: Sławomir Lasota


The course is a natural continuation of Introduction to Electronics. To provide more sophisticated methods of a calculation, derivation and estimation of parameters of circuits that are necessary in the designing of analog electronic circuits. Course description

An analysis of electronic circuits – the Sigorski method: basics, cofac-tors & determinants; computer symbolic analysis. Models of compo-nents: passive components; active components; op-amp (an ideal op-amp in the Sigorski method, coping with controlled sources, the stabil-ity problem in circuits with op-amps). Distortion in electronic circuits: estimation with the 3- & 5-point method; weak harmonic and inter-modulation distortion in BJT & MOS transistors; the influence of negative feed-back for harmonic and intermodulation distortion; fre-quency analysis of non-linear circuits – the harmonic balance method. Temperature vs. Q-operation point: 2 basic approaches – the potential node method and the superposition method; temperature models of semiconductor components. The sensitivity analysis and its applica-tion: basics; sensitivity in frequency domain; sensitivity in time do-main; sensitivity vs. accuracy of network functions (the worst case approach, statistical approach for large series); sensitivity vs. tempera-ture & power supply influence for network functions. Noise: Power Spectral Density vs. Root Mean Square; an analysis of circuits having noise sources; noise sources – components’ models; noise optimiza-tion. Coupling noise. Reliability in electronic circuits: constant failure rate; mean time to failure; the reliability function. An oscillator as resistance (capacitance) to frequency converter: quasi-linear model of


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oscillations; linear & non-linear frequency correction; long-term in-constancy vs. environmental influence; short-term inconstancy vs. phase noise.



M2.21 Computer aided electronic circuits design 7 30 15 3

Lecturer: Jacek Izydorczyk


The aim of the course is to give a general outlook on algorithms and techniques used for computer aided electronic circuits analysis and design. The course is concerned on circuit simulation techniques based on solving of differential equations. Course description

The purpose of the course is to familiarize students with primary algo-rithms and techniques used for computer aided electronic circuits analysis and design. The guide is famous SPICE program widely used by computer aids for circuit design for circuit simulation. The course covers following topic: Numerical analysis of linear cir-cuits: formulation of algebraical circuit equations; general characteri-zation of linear circuits; nodal equations; modified nodal equations; two-graph modified nodal equations; tableau equations; frequency domain a.c. circuit analysis; a.c. analysis of linear circuits; small-signal frequency analysis of nonlinear circuits. Numerical solution of linear algebraic equations: introduction to simultaneous linear alge-braic equations; finite methods of solving linear algebraic equations; gaussian elimination; LU factorization methods; numerical difficulties in the LU method. D.C. analysis of nonlinear circuits: a basic new-ton-raphson method; the case of a single nonlinear equation; NR method for a system of algebraic equations; methods for automatic formulation of iterative equations; realization of the basic D.C. analy-


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sis algorithm; practical quasi-newton-raphson algorithms; numerical problems with the basic NR algorithm; technique of NR step limiting on nonlinear elements. Time-domain analysis of nonlinear circuits: basic polynomial methods; realization of an algorithm for integrating OAED; BDF based on newton's interpolation; formulation of circuit equations for time-domain transient analysis; the companion circuit method; numerical problems due to selection of state variables; accu-racy of differentiation formulae; theory of the local truncation error; a LTE controlled variable step time-domain analysis; global properties of differentiation formulae; stability of differentiation formulae; con-vergence of differentiation formulae.



M2.22.1 Digital circuits design I 7 30 15 30 6 M2.22.2 Digital circuits design II 8 30 30 7 Lecturer: Tomasz Garbolino


The goal of the lecture is to extend a knowledge concerning design of digital circuits acquired by students during previous courses: Theory of Logic Circuits and Digital Circuits. The main goal of the second part of the course is to introduce students to fundamental aspects of designing digital circuits with the use of VHDL. The subject matter of the lecture encompasses – among other things – the VHDL language data structures and constructs that are useful in digital logic modelling for synthesis purposes and in design verification. Some introductory information about ASIC and FPGA technologies and VLSI design low is also provided.


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Course description

The lecture encompasses, among other things, problems connected with designing advanced arithmetic modules and circuits implement-ing time dependencies between signals. It also provides students with introductory information about synchronizing two digital systems op-erating with different frequencies or throughputs. Lecture curriculum: Advanced arithmetic modules: a) adders: carry save, carry select and carry look-ahead adders; b) multipliers: matrix combinational multi-plier, iterative combinational multiplier, sequential; shift & add multi-plier, sequential Booth's multiplier; c) dividers: combinational and sequential compare, subtract & shift dividers BIN / BCD and BCD / BIN converters Counter- and shift register-based circuits implementing time depend-encies between signals: a) univibrators, circuits differentiating signal edges, circuits delaying signal edges; b) pulse selectors, pulse distribu-tors; c) programmable pulse generators Basic synchronisation issues: a) metastability; b) passing data and control signals between different clock domains; c) synchronising data source and sink operating with different throughput; d) trouble-free switching between clocks VLSI design flow Introduction to CMOS technology Fundamentals of FPGA devices VHDL – overview and application field VHDL language and syntax: a) general language properties, identifi-ers, naming convention; b) structural elements; c) data types and op-erators; d) concurrent and sequential statements; e) RTL-style; f) sub-programs Simulation: a) sequence of compilation; b) simulation flow; c) process execution; d) delay models Introduction to design verification – writing testbenches Design synthesis




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M2.23 Electromagnetic field the-ory 7 30 30 5

Lecturer: Andrzej Karwowski


The main objective of the course is to introduce , in a unified manner, the fundamental concepts and the elements of the governing theory of electromagnetism, and to apply them to the analysis of wave propaga-tion phenomena, and – to a certain degree – to the analysis and design of radiating, scattering and guiding structures. Applications are made to some of the most basic and practical cases and configurations Course description

The subjects covered, besides a brief review of static electric field, steady electric current, and static magnetic field, include time-varying fields and Maxwell’s equations – in particular Faraday’s law of elec-tromagnetic induction, Maxwell’s equations in both differential and integral forms, potential functions, electromagnetic boundary condi-tions at media interface, wave equations and their solutions, and use of phasors for time-harmonic fields. Emphasis is then placed on plane electromagnetic wave and its properties – specifically on description of plane waves in lossless and conducting media, polarization of plane waves flow of electromagnetic power and Poynting vector, reflection (and transmission) of electromagnetic waves at a plane boundary be-tween two media. The course also includes theory and application of transmission lines, i.e., general transmission-line equations, transmis-sion line parameters, wave characteristics on an infinite transmission line, lines with arbitrary terminations, transmission lines as circuit elements, the Smith chart and Smith-chart calculations for lossless lines, transmision-line impedance matching (a quarter-wave trans-former, and single-stub matching). The course is completed by basic concepts related to antennas, and Friis transmission equation.


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M2.24 Theory of information and coding 7 30 2

Lecturer: Jerzy Rutkowski

Course description

Transmission of information or data from one point to another is one of the most important tasks in the modern world. This data can be transmitted on a very short distance, as inside a computer, or on a very long distance, as in a space communication. For somebody dealing with communication systems on a professional level essential knowl-edge of information and coding theory seems to be indispensable. However, this knowledge can be useful not only in communication systems but also in other various fields, such as for instance data com-pression, digital systems or design of experiments. This course is designated primarily for the second or third year stu-dent. It is assumed that students have some understanding of freshman calculus and elementary probability. The major results of the theory are quite subtle and abstract, and to make them easy to comprehend numerous examples have been provided. The course does not contain proofs of theorems, as they can be found in many, commonly avail-able books dealing with the same subject. On the other hand all the theorems and definitions are illustrated by many practical examples. The course consists of three parts. In Part I, theoretical description of entropy and information is pre-sented, for memory less and Markov sources, first for discrete sources then for continuous sources. Part II is devoted to coding and decoding of information. First, non-redundant codes are described, then error detecting and correcting codes. For the latter codes, first, general rules of coding and decoding are presented. Then, specific codes are described, one by one, starting from the most commonly used. In Part III, essential theory of the transmission channel is provided.


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Course load


ECTS

M2.26 Radiocommunication 7 30 15 4 Lecturer: Mirosław Magnuski


The aim of the course is to present the basic knowledge about RF de-vices and systems and to give fundamentals of designing of radio links. Course description

Transmitters, receivers and antennas: construction, properties, pa-rameters. Noise in receiving systems: noise sources, signal to noise ratio, noise factor, four noise parameters, circles of constant noise fig-ure. The wave approach to RF devices and systems: scattering pa-rameters, signal-flow graphs, Mason’s rule, generalised scattering matrix, definitions of power gain. Propagation: budget of a radio link, free space loss, properties of troposphere, curvature of a ray beam, K factor, Wwiedenski’s equations, Van der Pool’s equation, general model of propagation, Fresnel’s zones, knife edge obstacle, Ocu-mura’s budget of a radio link, ITU recommendation P.370-7.



M2.27 Bionics 8 30 15 4 Lecturer: Ewaryst Tkacz


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Course description

The main aim of the subject is to acquire an ability of considering properties of biological systems, their characteristic as well as most important features from both mathematical and physical modeling point of view. The further aim concerns future application of such knowledge to improve a quality of widely understand diagnostic proc-ess. Short description of contents Basic knowledge concerning general system theory Homeostatic systems Electrical activity of cells and tissues Hodgkin-Huxley biological excitability theory Biological systems functions and their modeling Biological signals Technical assistance of biological inner organs (both long and short term heart support) Limbs prostheses



M2.50 Computer networks II 8 30 2 Lecturer: Mirosław Skrzewski

Course description

This course on Computer Networks presents advanced topics related to networking, protocol stack architectures and networking services: principles of point-to-point communication, basic rules included in low-level protocols – block transmission, error correction, block / ac-knowledgement identification, protocol transparency, frame transmis-sion, sliding window principle, piggy-back / group acknowledgement, group retransmission, flow control. Multi-access channels, media access protocols for radio (ALOHA, CSMA/CA), wire (CSMA/CD, reservation, token passing) and ring topology (Cambridge Ring, Token Ring) channels.


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Channel length limitation, communication subnets, channel switching, information (message, packet) switching, connection, connection-less transmission. Routing, distribution of routing information, routing algorithms – flooding, fixed route, adaptation protocols, routing information gather-ing. Information transport problems and solutions. End-to-end flow control, methods of network congestion prevention. ISO OSI Reference Model architecture; layer-to-layer communication, data encapsulation, layer addressing, error checking, transmission primitives. Transport, session, presentation, application layers and their functions in ISO architecture. Examples of network architectures. XNS (NetWare) stack of proto-cols, principles of systems communication, network addressing, ser-vices access. Organization of date exchange in NetWare systems, pro-tocol modification (IPX, SPX, SAP, RIP), assigned numbers. DoD architecture – protocols IP, ICMP, TCP, UDP, ARP, network addressing, services access, naming convention, name to address translation (DNS). NetBIOS protocol, name space, name to address conversion, NetBIOS over IPX, NetBIOS over TCP. NetBIOS related services in Windows XX systems, SMB protocol. Client-server versus peer-to-peer architecture. Internet services or-ganization – http, ftp, mail, telnet, rpc as examples of client-server architecture. Problems of security in network services – protocols with information encryption – ssh, IPsec, PPTP, VPN. Architecture of network access (last mile architecture). Modem access – SLIP, PPP protocols, ISDN, broadband access – xDSL protocols, cable modem access. Access address distribution, dynamic or static IP addressing, bandwidth distribution. User access security – packet fil-tration (firewall) systems, network address translation.



M2.28.1 Exchange devices I 8 30 2 M2.28.2 Exchange devices II 9 45 4


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Lecturer: Jerzy Wojtuszek

Course description

Subscriber line signalling. Calling party side – seizure, dial tone, decadic dialling, DTMF dial-ling, ringing tone, answer, clear signal, on-hook signal, metering pulses, tone and spoken (recorded announcements) information sig-nals. Called party side – ringing signal, answer signal. Structure and performance of telephone set. Block diagram of simple telephone set, receiving of ringing, sending off-hook signal, sending dialling signals, receiving of acoustic signals, acoustic to electric conversion, anti-side tone circuit. Line unit. BORSCHT functions (Battery, Overvoltage, Ringing, Supervisory, Coding, Hybrid, Testing). Battery and supervisory based on discrete components, supervisory during ringing. Specialized integrated cir-cuits: Motorola MC3419 (SLIC), Intel 2912 (filter), Intel 2911 (co-dec), methods of sending ringing signal (relay or opto-triac). Space-division switching network. Physical realization, connecting subscibers to two-sided switching network and connection set-up, state of blocking. Clos switching net-work and Clos theorem. Time division switching networks. S-T-S (Space-Time-Space) and T-S-T (Time-Space-Time) switching networks – time switch, time multiplexed switch, structures of S-T-S and T-S-T networks, space equivalents of S-T-S and T-S-T networks, conditions for non-blocking. Switching networks based on integrated switches – structure and per-formance of integrated switch, limits for number of inputs and out-puts, arrangement of non-blocking networks composed of integrated switches. ISDN networks. User-network interfaces (2B+D and 30B+D). Structure of customer equipment (U, T and S reference points, network terminations NT1 and NT2, terminals TE1 and TE2, terminal adapter TA, power sup-ply). Line codes and time frames for U and S/T reference points. D-channel contention resolution. LAPD protocol – frames and proce-


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dures. EDSS1 protocol – messages and procedures for connection establishment and clearing, Echo cancellators and scramblers.



M2.29 Java and programming in the Internet 8 30 30 4

Lecturer: Krzysztof Dobosz


In the framework of the subject, the Java programming language will be presented with its means, tools and methods that enable building programs destined for exploitation both as the Internet and standalone applications. Among others, mechanisms for error handling, multi-threading and network protection will be exposed, also fundamentals of enterprise applications and application for mobile devices will be presented. Course description

During the course following lecture subjects are realized: general lan-guage description; similarities and differences as opposed to the C++; Java as a re-usable component language; realization of the object pro-gramming idea in Java; object member data organization, inheritance mechanism; built-in data types; defining classes – general rules; prin-ciples of access to member elements; creating and deleting objects. method defining – non-elementary cases; ways of parameter passing; Special cases of inheriting member elements: end components, final components; abstract classes, interfaces, exception handling; mecha-nisms for multithreading organization; threads synchronization, star-vation, deadlock and other multithread problems; building program-ming environments using components from the Java Foundation Class (JFC) package; graphical user interface designing with AWT, Swing and SWT components; layout managers; mechanisms for event han-


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dling; basic rules for building and executing applets; I/O operation organization; methods of application intercommunication based on streams and sockets; serialization; data processing in streams; Java servlets technology in enterprise applications; Java Native Interface - using native libraries in Java applications; fundamentals of Java 2 Mi-cro Edition platform; general rules for mobile devices programming, midlet lifecycle; general description for multimedia home platform; collection framework and design patterns in Java. Practical part of the course contains: 6 subject units: (1) Getting ac-quainted with the JDK (Java Development Kit) package and the Eclipse program development environment. Executing a simple stand-alone application and an applet. Modifying sample applications; (2) Building multithreading applications (3) Building graphical user inter-faces in window technology using Swing components; technique. (4) Building applications intercommunicated by means of streams and sockets, using higher and lower level operations to handle network connections with TCP and UDP protocols; (5) Developing applica-tions server using the Java Servlets; (6) Programming mobile phones using Java 2 Micro Edition standard library.



M2.31 Wireless computer net-works 8 30 2

Lecturer: Bartłomiej Zieli�ski

Course description

Reasons for the usage of wireless transmission media. Opportunities of wireless media application, examples. Introduction to wireless me-dia characteristics, electromagnetic waves division. Radio waves characteristics. Bands division. Propagation classifica-tion. Propagation description for waves: long, medium, short, ul-trashort and microwaves. Radio waves utilisation for data transmis-


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sion. Modulation methods. Radiocommunication system parameters design. Spread spectrum systems. Optical waves characteristics. Infrared and laser waves properties. Modulation in optical systems. Optical links classification. Law re-strictions and general technical parameters of wireless links. Medium access protocols in wireless local networks. The need for new protocol definition: hidden and exposed nodes, capture effect, interference. Protocol properties: Aloha, CSMA, BTMA, SRMA, MSAP, MACA, MACAW, FAMA and BAPU. Efficiency comparison for the most important protocols. Survey of wireless transmission hardware. Classifications. Radio-modems and optical modems. Packet controllers. TNC controllers. Comparisons of selected products. Survey of wireless transmission hardware. Bridges. Network adapters. Other solutions. Comparisons of selected products. Survey of wireless digital transmission systems. Classifications. Cord-less and cellular telephony. Trunked networks. Wide area stationary networks. Wide area mobile networks. Local area networks. GSM; cellular telephony standard. DECT; cordless telephony stan-dard. Modern data transmission in telephony systems (HSCSD, GPRS). Stationary wide area networks ; Aloha, Packet Radio. Mobile wide area networks ; Mobitex, CDPD. TETRA ; trunking network standard. Local area networks ; American standards: IEEE 802.11, 802.11a, 802.11b; European standards: HiPeRLAN, HiPeRLAN/2. Personal area networks ; IrDA and BlueTooth systems. IEEE 802.15 WPAN standard. Wired and wireless network integration. Problem genesis. Connection methods on physical or logical link layers level. Hardware and soft-ware structure. Protocol converter for RS-232C link. Hardware and software con-struction, operation rules, efficiency. Protocol converter for industrial networks. Converter for multisegment Modbus network. Network efficiency in presence of converters ; RS-232 link, Modbus network with one and many segments. Computing power and trans-mission efficiency. Further research over protocol converters.


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M2.51 Cellular phone systems 8 30 2 Lecturer: Andrzej Karwowski


The main objective of the course is to introduce the student into cellu-lar radio and wireless personal communications, specifically into cel-lular phone systems, one of the fastest growing fields in the engineer-ing world. The course covers basic technical concepts being the core of design, implementation, research, and invention of cellular teleph-ony, as well as those specific to particular systems and standards.

Course description

The course covers the fundamental concepts of handoff, frequency reuse, trunking efficiency, and frequency planning. The course starts with explaining the cellular concept (cellular system topography, hex-agonal geometry, cells, clusters, co-channel cells, frequency reuse concept); signal-to-interference ratio, co-channel interference and sys-tem capacity, frequency reuse factor, adjacent channel interference, methods for reducing interference; basic concepts and terms used in trunking theory (traffic intensity, offered traffic, grade of service, etc.; blocked calls cleared systems (Erlang B systems), blocked calls de-layed systems (Erlang C systems)); improving capacity in cellular systems (cell splitting, sectoring, micro- and pico-cell zone concept). Then basic propagation mechanisms (reflection, diffraction, and scat-tering) and relevant models for predicting signal strength are dis-cussed, namely, free space propagation model, ground reflection (2-ray) model, diffraction and Fresnel zone geometry, knife-edge diffrac-tion model, scattering and the Rayleigh criterion. Practical link budget design using path loss models (Okumura, Hata, etc.) are also demon-strated, and the effects of small-scale fading and multipath are ad-dressed. Another part of the course covers a brief review of modula-


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tion techniques for mobile cellular telephony (analog and digital modulation, pulse shaping techniques, linear modulation techniques (BPSK, DPSK, QPSK, etc.), constant envelope modulation (MSK, GMSK), and spread spectrum modulation techniques (DS-SS, FH-SS), and multiple access techniques for wireless communications starting from FDD through FDMA, TDMA up to CDMA and WCDMA. The course is completed by a compilation of the major ex-isting and proposed cellular and personal communications systems and standards.



M2.32 Digital and analog telecom-munication 9 30 15 15 6

Lecturer: Jacek Izydorczyk


The aim of the course is to give a general outlook on communication media, modern modulation techniques, channel equalization, carrier and symbol synchronization and channel coding. Course description

The purpose of the course is to familiarize students with primary con-cepts and principles of contemporary communications in the physical and link layer of ISO/OSI model. Different types of communication techniques from modulation to media sharing are presented. The course covers following topic: ISO/OSI model of communica-tion system: services of physical layer; data link layer, network layer; transport layer, session layer, presentation layer and application layer – illustrated by non-technical examples. Communication Channels and Their Characteristics: copper media – coaxial cable; waveguide and modes of EM waves; fibre-optic cable; emission of EM waves by wires with current; a simple model of radio waves propagation; line-


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of-sight radiolink, Fresnel zones, wet floor effect, fading. Characteri-zation of Communication Signals and Systems: representation of band-pass signals and systems – Hilbert transformer and its impulse response; signal space representations; representation of digitally modulated signals; spectral characteristics of digitally modulated sig-nals. Amplitude modulation: baseband and carrier communication; amplitude modulation: double standard (DSB); amplitude modulation (AM); quadrature amplitude modulation (QAM); amplitude modula-tion: single sideband (SSB); amplitude modulation: vestigial sideband (VSB); carrier acquisition; superheterodyne AM receiver; television. Angle modulation: concept of instantaneous frequency; bandwidth of angle-modulated wave; generation of FM waves; demodulation of FM; interference in angle-modulated systems; FM receiver. Behavior of analog systems in the presence of noise: baseband systems; am-plitude-modulated systems; angle-modulated systems; pulse-modulated systems; optimum preemphasis-deemphasis systems. Op-timum receivers for the additive white gaussian noise channel: optimum receiver for signals corrupted by additive white gaussian noise; performance of the optimum receiver for memoryless modula-tion; optimum receiver for CPM signals; optimum receiver for signals with random phase in AWGN channel; performance analysis for wire-line and radio communication systems. Channel capacity and cod-ing: channel models and channel capacity; random selection of codes; communication system design based on the cutoff rate. Block and convolutional channel codes: linear block codes; convolutional codes; coded modulation for bandwidth-constrained channels - trellis-coded modulation. Carrier and symbol synchronization: signal pa-rameter estimation; carrier phase estimation; symbol timing estima-tion; joint estimation of carrier phase and symbol timing. Multiuser communications: introduction to multiple access techniques; capacity of multiple access methods; code-division multiple access; random access methods.



M2.35 Microelectronics 9 30 30 5


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Lecturer: Jacek Szuber


To acquaint the students with fundamentals of microelectronics and its applications in modern technology. Course description

Introduction to semiconductor microelectronics. Fundamentals of semiconductor, surfaces and interfaces. Technology of semiconductor single crystals for microelectronics. Technology and control of an ultrahigh vacuum for semiconductor nanotechnology. Technology of semiconductor thin solid films of special application. Fundamentals of semiconductor nanotechnology. Surface experimental techniques in semiconductor nanotechnology. Semiconductor microsystems and devices.



M2.37 Programmable logic de-vices 9 30 15 4

Lecturer: Józef Kulisz

Course description

Introduction Some general remarks on contemporary digital circuit design and manufacturing techniques: Catalogue Logic, Full Custom Integrated Circuits, Application Specific Integrated Circuits (ASIC-s). The ASIC techniques: Full Custom ASIC, Standard Cell, Gate Arrays, Pro-grammable Logic Devices (PLD-s). The concept of a Programmable


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Logic Device, explained using a simple FPLA device F100. PLD families: Simple PLD-s, Complex PLD-s (CPLD-s), FPGA-s. Simple PLD-s Simple PLD architectures: PAL, FPLA (PLA), PROM (PLE). Pro-gramming technologies used with SPLD-s: metal fuses, AIM (Ava-lanche Inducted Migration), ultraviolet erasable cells (EPLD-s), elec-trically erasable cells (EEPLD-s). An overview of PAL architectures: naming convention, PAL16L8 – the basic structure, programmable output polarity and its applications – PAL16P8, registered PAL-s – PAL16R4 – an example of a synchronous circuit implementation, ge-neric PAL-s – PAL22V10, a brief overview of complex PAL-s: the EP600, EP900, EP1800 devices from Altera, the Atmel 750, 1500 and 2500 devices. An overview of PLA architectures: PLA100 – the basic structure, PLS architecture – PLS159, implementation of synchronous FSM-s in PLS structures: state coding, illegal state recovery issues, some remarks on the Complementary Line and it’s applications, the Lattice 6001 device – an example of a complex PLA architecture. Some remarks on Folded NOR (Erasic XL78C800), and folded NAND architectures. A summary of SPLD features: process tech-nologies, programming technologies, some special features: Security Fuses, Power/Speed Selection Fuses; electrical parameters (propaga-tion delays, power supply); SPLD programming (parallel, ISP Serial), the JEDEC format; SPLD design flow, a simple design example, CPLD-s The general structure of a CPLD. Features of CPLD devices presented using the Altera Max 7000 family: the general architecture, the struc-ture of Logic Array Block (LAB), the structure of a macrocell, the XOR gate in a macrocell and its applications (an example), the con-cept of parallel and shareable expanders (an example), programmable Interconnect Array (PIA), the structure of I/O Control Blocks, electri-cal features of Max 7000 devices: logic standards accepted, power supplies, output control; timing model and propagation delays, an ex-ample of using the fast input, some remarks on datapath optimisation; A brief presentation of another CPLD families from Altera. A brief presentation of the Mach 4000 family from Lattice – another example of CPLD devices, the general structure, the structures of PAL Blocks and Macrocells, the concept of expanders implemented in Mach de-vices, the Output Switch Matrix and output routing. The architecture


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of XPLD (eXpanded Programmable Logic Devices) devices and product term sharing concept, presented using the ispXPLD family from Lattice. Programming technologies and programming procedures used with CPLD devices. FPGA-s The general structure of an FPGA device (CLB, routing channels, Switch Blocks, I/O Cells); Programming technologies used in FPGA devices: SRAM cells, antifuses, Fine granularity vs. Coarse Granular-ity architectures and their relation to programming techniques. The Xilinx Virtex family – an example of a coarse granularity device. the structure of a Configurable Logic Block (CLB), a slice, a LUT, differ-ent modes of operation of a slice, the structure of an I/O Block, pro-grammable interconnect resources. An example combinatorial func-tion implementation with decomposition to 5-input LUT-s; The con-cept of Fast Carry Logic – design examples; The other architecture features: block RAMs, Digital Clock Managers (DCM-s). FPGAs from Actel – an example of the antifuse devices: the general structure, the structures of Logic Modules, the structure of I/O Modules, the routing architecture. A short presentation of the Virtex II and Spartan 3 families form Xilinx, Design flow for CPLD and FPGA devices. Using VHDL for synthesis dedicated for PLD devices. Avoiding pit-falls in CPLD and FPGA design.

Postgraduate courses: Databases, Computer Networks and Systems



M2.35 Algorithm and Data Struc-tures 7 30 30 6

Lecturer: Wojciech Mikanik


The course offers students comprehensive overview of algorithms. The lecture covers basic concepts, algorithms and data structures, whi-le the classes give opportunity to practise the new skills and knowled-ge in practice Course description

The course provides the knowledge required to understand and cor-rectly use various algorithms and data structures. The course offers students knowledge needed to analyse algorithms on their own. The course covers the following topics: The notion of computational com-plexity; Min max search; Simple sorting algorithms; Quicksort and k-selection; Divide and conquer; Heap: priority queues, heap sort; Other sorting algorithms: bucket sort, radix sort; Searching: linear, binary; Binary search trees; Heaps; Hashing: open and closed, perfect hash-ing; Exhaustive search, branch and bound, alpha-beta cut; Greedy al-gorithms; Graph algorithms: BFS, DFS, shortest path, minimal span-ning tree; Pattern matching: brute force, KMP, BM.



M2.36.1 Computer architecture I 7 30 2 M2.36.2 Computer architecture II 8 30 3


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Lecturer: Krzysztof Trocki

Objectives of the course Course description

History of computer architecture and organization. Distinction between architectural and organizational attributes of computer systems. Elements of computer memory organization: Principle of locality of reference (spatial and temporal locality); Concept of virtual memory; Memory bandwidth and memory latency; Cache memory. Introduction to parallel processing: Various classifications of com-puter systems; First mechanisms of parallel processing; Theoretical boundaries of parallel processing; Concept of grain of parallelism; Concept of tightly coupled and loosely coupled computer design. Pipelining: Instruction pipelining; Arithmetic pipelining; Problems associated with pipelining (structural, data and control hazard). Vector computers: Memory-memory vector computers; Vector-register vector computers; Vector instruction set advantages; Over-view of techniques typically employed in vector computers design (stripmining, vector chaining, conditional vector execution, compress and expand, scatter and gather). Array computers: General design of array computers (Distributed Memory and Shared Memory approach); Interconnection networks; Examples of programs executed on array computers. Multiprocessors & Multicomputers: Classification of Multiple Instruc-tion Multiple Data Streams (MIMD) computers; Interconnection net-works; Processors for MIMD architectures; Uniform Memory Access (UMA) computers (Parallel Vector Processors, Symmetric Multiproc-essors); Non-Uniform Memory Access (NUMA) computers (Cache Only Memory Access, Cache Coherent NUMA, Non-Cache Coherent NUMA, Software-Coherent NUMA); No-Remote Memory Access (NORMA) computers (Clusters, Massively Parallel Processors). Modern general-purpose processors: Complex Instruction Set Com-puters vs Reduced Instruction Set Computers approach; Post-Reduced Instruction Set Computers / Fast Instruction Set Computers approach; Multimedia / Single Instruction Multiple Data streams extensions;


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Limitations of current design of modern general-purpose processors; Very Large Instruction Word (VLIW) / Explicitly Parallel Instruction Computing (EPIC) approach.



M2.37.1 Digital modelling and sim-lation I 7 30 30 4

M2.37.2 Digital modelling and simulation II 8 30 3

Lecturer: Tadeusz Czachórski


The lecture is an introduction to the problems of modelling and per-formance evaluation of computers and computer networks. Perform-ance evaluation is required at every stage in the life cycle of a com-puter system or network, including its design, manufacturing, sales/purchase, use, and upgrade. Course description

As the field of computer design matures, the computer industry is be-coming more competitive, and it is more important than ever to ensure that the alternative selected provides the best cost-performance trade-off. The same applies to computer networks, especially to wide area communication networks. The lecture examines the main modelling methods based on queueing theory and illustrates them with typical examples and case studies to demonstrate their utility in investigation of real-life problems encountered in sizing computers and computer networks, especially based on Internet protocols TCP/IP and ATM protocol. The material covers the following topics. Operational mod-els - basic laws: utilization law, forced flow law, Little's law, general response time law, interactive response time law; asymptotic bounds, balanced job bounds. Mean Value Analysis (MVA) and related tech-niques: MVA for one class of customers (open and closed networks),


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MVA for multiple classes of customers (open, closed and mixed net-works), approximate MVA. Applications in modelling virtual paths and window mechanism in computer networks. Analysis of a single Markov queueing system: Markov chains with continuous and discrete time, Chapman-Kolmogorov equations, queues of the type M/M/1, M/M/c, M/M/1/K, M/M/1//H, M/M/c/K/H; their analytical solution and applications to model parallel execution, finite buffer effects, fi-nite population of executed processes; queues with Erlang (E) and Cox (C) distributions M/E/1, E/E/1, C/C/1. Markov models of self-similar network flows, Markov models of chosen quality of service and flow control mechanisms, e.g. RED queue, leaky bucket with tokens mechanism. Introduction to numerical methods and related software to solve numerically very large Markov models. Markov queueing networks: open and closed queueing networks, product form solutions, global and local stability, convolution algorithm, BCMP model; hierarchical decomposition of large queueing networks. Single station analytical non-Markov models: M/G/1, G/M/1, G/G/1; appli-cations to model a disc station, a token-ring local network. Diffusion approximation method - steady state and transient solution to a net-work of G/G/1 and G/G/1/N stations with one or multiple classes of customers. Application to model mechanisms of congestion control at communication networks: at the entrance to a network (jumping win-dow, sliding window and leaky bucket mechanisms), at a node (push-out and threshold space priority algorithms), and between nodes (reac-tive closed-loop mechanisms based on congestion notification). Basic notions of discrete-event simulation, e.g confidence interval and con-fidence level of simulation results, an introduction to OMNET++ simulation package.



M2.38.1 Programming in assembler I 7 30 2

M2.38.2 Programming in assembler II 8 30 3


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Lecturer: Krzysztof Tokarz

Course description The course on Programming in Assembler concerns the following groups of topics from the 8086 family microprocessors' programming: Introduction. Assembler in information technology and programming languages. 8086 family architecture. From 8086 to Pentium4. Regis-ters, flags, memory organization. Logical, physical, effective address. Addressing modes. Memory models. I/O addressing. Interrupts and exclusions. Data types. Format of the instruction. Instructions. General purpose instructions. MASM. General components. Operators. Identi-fiers. Statements. Directives. Memory models. Simplified segment directives. Full segment definitions. Procedures. Parameters. Modules. Directives. Defining and using simple and complex data types. Type operators. Decision directives. Loops. Text macros. Macro proce-dures. String directives. Macro functions. Floating point coprocessor instructions. MMX instructions. Mixed language programming. C and Basic to MASM Interface. Writting Windows 32 applications. Writ-ting dynamic libraries. The course lecture is accompanied by a set of laboratory exercises concerning basic and advanced assembler language programming top-ics: Installation and configuration of MASM 6.14 with Programmer's Workbench environment. Installation and configuration of MASM32v8. Usage of programming and debugging tools. Writting and debugging simple MS-DOS programs. Understanding program segments. Writting procedures with extended PROC statement and INVOKE directive. Writting macros. Interrupt handling. As a part of the laboratory students are to write their own application using chosen assembly environment (MASM 6.14 PWB or MASM32).



M2.39.1 Software engineering I 7 30 2 M2.39.2 Software engineering II 8 30 3


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Lecturer: Przemysław Szmal


The aim of the course is to present a review of selected problems in software engineering. Course description

The course gives introduction to the following topics: - Software life-cycle, software production process management. Struc-tural and object-oriented approach to software system elaboration. Notation. - Requirements definition, building analytical models. Reviews in the software production process. Introduction to UML. Design – essence, organization, realization. Software quality estimation. Programming style. Testing rules, testing stages. Testing ideas, preparing data for testing. Debugging – approach, estimation of quality. Measuring software efficiency, optimization, reliability. Improving fault tolerance; defensive programming. Lectures: Introduction, the scope of interest of Software Engineering Software crisis, software life-cycle models Managing a software project Strategy phase Requirements definition phase CASE tools in the strategy and requirements definition phases Analysis phases, system project, structural methodics part1 Structural methodics part 2 Object methodics (before UML) The UML language and methodics, part 1 The UML language and methodics, part 2 Implementation, testing


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M1.17.2 Computer networks II 8 30 30 6 Lecturer: Mirosław Skrzewski

Course description

This course on Computer Networks presents advanced topics related to networking, protocol stack architectures and networking services: principles of point-to-point communication, basic rules included in low-level protocols – block transmission, error correction, block / ac-knowledgement identification, protocol transparency, frame transmis-sion, sliding window principle, piggy-back / group acknowledgement, group retransmission, flow control. Multi-access channels, media access protocols for radio (ALOHA, CSMA/CA), wire (CSMA/CD, reservation, token passing) and ring topology (Cambridge Ring, Token Ring) channels. Channel length limitation, communication subnets, channel switching, information (message, packet) switching, connection, connection-less transmission. Routing, distribution of routing information, routing algorithms – flooding, fixed route, adaptation protocols, routing information gather-ing. Information transport problems and solutions. End-to-end flow control, methods of network congestion prevention. ISO OSI Reference Model architecture; layer-to-layer communication, data encapsulation, layer addressing, error checking, transmission primitives. Transport, session, presentation, application layers and their functions in ISO architecture. Examples of network architectures. XNS (NetWare) stack of proto-cols, principles of systems communication, network addressing, ser-vices access. Organization of date exchange in NetWare systems, pro-tocol modification (IPX, SPX, SAP, RIP), assigned numbers. DoD architecture – protocols IP, ICMP, TCP, UDP, ARP, network addressing, services access, naming convention, name to address translation (DNS).


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NetBIOS protocol, name space, name to address conversion, NetBIOS over IPX, NetBIOS over TCP. NetBIOS related services in Windows XX systems, SMB protocol. Client-server versus peer-to-peer architecture. Internet services or-ganization – http, ftp, mail, telnet, rpc as examples of client-server architecture. Problems of security in network services – protocols with information encryption – ssh, IPsec, PPTP, VPN. Architecture of network access (last mile architecture). Modem access – SLIP, PPP protocols, ISDN, broadband access – xDSL protocols, cable modem access. Access address distribution, dynamic or static IP addressing, bandwidth distribution. User access security – packet fil-tration (firewall) systems, network address translation. The course lecture is accompanied by a set of laboratory exercises, presenting advanced topics of protocol services interface (API) and client-server programming, services configuration and network traffic monitoring.



M2.40.1 Concurent programming I 8 30 30 4 M2.40.2 Concurent programming II 9 30 3 Lecturer: Wojciech Mikanik


The course offers students comprehensive overview of concurrent programming. The lecture covers basic concepts and mechanisms, while the classes give opportunity to practise the new skills and knowledge in practice.

Course description

The course provides the knowledge required to understand, design and develop concurrent programs. The course covers the following topics: Introduction to concurrency. How to specify concurrent execution.


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Shared memory model: communication and synchronization using semaphores and monitors. Distributed memory model: communication and synchronization via message passing, RPC. Guarded commands. Properties of concurrent programs and their correctness. Lectures are illustrated with many sample programs. The second se-mester of the course offers students an occasion to create programs on their own during laboratories.

Course load (hours per semester) ID Course Semester L P Lab

ECTS

M2.41.1 Introduction to compilers I 8 30 2 M2.41.2 Introduction to compilers II 9 30 2

Lecturer: Przemysław Szmal


Aim of the subject: The aim is to present selected problems connected to programming language description and compiler construction. The student masters algorithms and methods for lexical and syntactic analysis, as well as ways of extending them for translation purposes. Topics suitable for construction of simple translators met in program-mer’s practice – command interpreters, macro-generators, linkers and so on – are covered.

Course description

In the framework of the lecture the following topics will be discussed: Essence of programming language machine translation: generating equivalent programs expressed in another language. Lexical, syntactic and semantic layers of programs. Connections with the construction of the language virtual machine. Characteristic stages in translating programs to target form: compilation and its phases, consolidation. Translation schema variants. Language description methods and using them in the text analysis stage. Formal grammars, Chomsky’s classification.


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Lexical layer of programming languages – regular grammars. (Stack-less) finite-state automata – nondeterministic, deterministic; building, transforming, optimization, application in the course of lexical analysis. Lex, the lexical analyser generator. The syntactic layer – context-free grammars. Grammar transformations: left recursion elimination, (left) factorisation, disambiguation. Top-down syntax analysis: deterministic analysers based on the recursive descent principle, non-recursive predictive analysis; LL-grammars. Construction of parse-driving table. Bottom-up syntax analysis. Operator-precedence grammars – analysis algorithm, constructing parse-driving table. Evaluating precedence functions. LR-grammars. Analysis algorithm, constructing simple (SLR) canonical (LR), look-ahead (LALR) LR-analysers. Building translators with use of the yacc generator: introducing semantic actions through translation schemata. Error handling: detection and diagnosing, error recovery and correction.



M2.29 Java and internet program-ming 8 30 30 4

Lecturer: Krzysztof Dobosz


In the framework of the subject, the Java programming language will be presented with its means, tools and methods that enable building programs destined for exploitation both as the Internet and standalone applications. Among others, mechanisms for error handling, multi-threading and network protection will be exposed, also fundamentals of enterprise applications and application for mobile devices will be presented.


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Course description

During the course following lecture subjects are realized: general lan-guage description; similarities and differences as opposed to the C++; Java as a re-usable component language; realization of the object pro-gramming idea in Java; object member data organization, inheritance mechanism; built-in data types; defining classes – general rules; prin-ciples of access to member elements; creating and deleting objects. method defining – non-elementary cases; ways of parameter passing; Special cases of inheriting member elements: end components, final components; abstract classes, interfaces, exception handling; mecha-nisms for multithreading organization; threads synchronization, star-vation, deadlock and other multithread problems; building program-ming environments using components from the Java Foundation Class (JFC) package; graphical user interface designing with AWT, Swing and SWT components; layout managers; mechanisms for event han-dling; basic rules for building and executing applets; I/O operation organization; methods of application intercommunication based on streams and sockets; serialization; data processing in streams; Java servlets technology in enterprise applications; Java Native Interface - using native libraries in Java applications; fundamentals of Java 2 Mi-cro Edition platform; general rules for mobile devices programming, midlet lifecycle; general description for multimedia home platform; collection framework and design patterns in Java. Practical part of the course contains: 6 subject units: (1) Getting ac-quainted with the JDK (Java Development Kit) package and the Eclipse program development environment. Executing a simple stand-alone application and an applet. Modifying sample applications; (2) Building multithreading applications (3) Building graphical user inter-faces in window technology using Swing components; technique. (4) Building applications intercommunicated by means of streams and sockets, using higher and lower level operations to handle network connections with TCP and UDP protocols; (5) Developing applica-tions server using the Java Servlets; (6) Programming mobile phones using Java 2 Micro Edition standard library.


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M2.31 Wireless computer net-works 8 30 2

Lecturer: Bartłomiej Zieli�ski

Course description

Reasons for the usage of wireless transmission media. Opportunities of wireless media application, examples. Introduction to wireless me-dia characteristics, electromagnetic waves division. Radio waves characteristics. Bands division. Propagation classifica-tion. Propagation description for waves: long, medium, short, ul-trashort and microwaves. Radio waves utilisation for data transmis-sion. Modulation methods. Radiocommunication system parameters design. Spread spectrum systems. Optical waves characteristics. Infrared and laser waves properties. Modulation in optical systems. Optical links classification. Law re-strictions and general technical parameters of wireless links. Medium access protocols in wireless local networks. The need for new protocol definition: hidden and exposed nodes, capture effect, interference. Protocol properties: Aloha, CSMA, BTMA, SRMA, MSAP, MACA, MACAW, FAMA and BAPU. Efficiency comparison for the most important protocols. Survey of wireless transmission hardware. Classifications. Radio-modems and optical modems. Packet controllers. TNC controllers. Comparisons of selected products. Survey of wireless transmission hardware. Bridges. Network adapters. Other solutions. Comparisons of selected products. Survey of wireless digital transmission systems. Classifications. Cord-less and cellular telephony. Trunked networks. Wide area stationary networks. Wide area mobile networks. Local area networks. GSM - cellular telephony standard. DECT - cordless telephony stan-dard. Modern data transmission in telephony systems (HSCSD, GPRS).


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Stationary wide area networks - Aloha, Packet Radio. Mobile wide area networks - Mobitex, CDPD. TETRA - trunking network standard. Local area networks - American standards: IEEE 802.11, 802.11a, 802.11b; European standards: HiPeRLAN, HiPeRLAN/2. Personal area networks - IrDA and BlueTooth systems. IEEE 802.15 WPAN standard. Wired and wireless network integration. Problem genesis. Connection methods on physical or logical link layers level. Hardware and soft-ware structure. Protocol converter for RS-232C link. Hardware and software con-struction, operation rules, efficiency. Protocol converter for industrial networks. Converter for multisegment Modbus network. Network efficiency in presence of converters - RS-232 link, Modbus network with one and many segments. Computing power and trans-mission efficiency. Further research over protocol converters.



M2.52 Face Recognition and Bio-metric Systems 8 30 30 4

Lecturer: Michał Kawulok

Course description

In recent years a sudden development of the market dealing with bi-ometry can be observed and probably a demand for computer systems of identification will be still increasing. The aim of this subject is to present the principal technologies used in the biometry and prepare the students for designing and building advanced biometric systems. The students will be familiarised with technical know-how obtained during the implementation of already working automatic face recognition system. Moreover, the best students will be given an opportunity of cooperation with a company dealing with computer vision and face recognition. The lecture will address the issues concerning biometric systems, par-ticularly concentrating on face recognition problems. The laboratory


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classes will provide a possibility of implementing the main phases of face recognition described during the lecture. The students will create or modify components of an existing system, which will make it easier to test and assess the effectiveness of applied methods and solutions.



M2.43 Computer graphics and vision II 9 30 30 6

Lecturer: Leszek Luchowski

Course description

Textures: definition, types of texture, texture mapping, texels, mip maps, statistical texture analysis (first- and second- order statistics) Fractals: definition, examples, history of fractals, Cantor set, Koch snowflake, Sierpinski carpet, Iterated Function System with Probabil-ity, Mandelbrot set (method, algorithm), Hausdorff dimension Ray tracing: ray tracing and radiosity methods. Image segmentation: thresholding, edge detection, contour tracking. Deformations of geometric shapes: Shape and Form; Size measures; Optimal superposition vs baseline superposition; Procrustes Analysis; Dilatation, dilatation tensor; Multilevel deformation analysis. Active Appearance Models: Active models: snake (active contour), Active Shape Model and Actie Appearance Model. Stereo matching: Cepstral matching. Hierarchic approach. Creating disparity maps. Projective geometry: Relations between the 3D scene and its projected images. The epipolar constraint. Fundamental matrix. Calibration and Reconstruction: Identifying the parameters relating the image to the scene. Using them to locate points in 3D. 3D scene integration: Architecture of active vision system, Algorithm for integration of 3D scene model, representations of geometric ob-jects, graph representation of scene structures, matching graph struc-


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tures, matching strategy and constraints (such as Procrustes distance), updating scene models Active Vision: Architecture, navigation algorithms, view-point selec-tion. 3D scanner: types of 3D scanners, methods of scanning, process of modeling surfaces, mesh and surface representation, registration and merging methods, Delaunay triangulation, software for 3D modeling. Computed Tomography: The idea of X ray Imaging; Introduction to Computed Tomography; Attenuation coefficients and CT numbers; Idea of reconstruction in CT: algebraic methods, Fourier methods; Radon transform, Sinogram; Central Slice Theorem; Generation of tomograms; Reconstruction of 3D surfaces from slices (Marching Cubes algorithm). Applications of computer vision: Intermediate-level vision tasks use-ful in technology. Practical uses in industrial inspection, automation, robotics, medicine, and other areas.



M2.44 DBMS Oracle 9 30 30 4 Lecturer: Bo�ena Małysiak


The subject is aimed to present chosen problems connected to the ORACLE relational database management system and tools in Devel-oper packet used to create applications.

Course description

Lecture of ORACLE database management system presents basic problems of administration of ORACLE database and tools used to create applications in DBMS ORACLE. Among presented problems of ORACLE database administrating there are described: system ar-chitecture, designing and creating database, management of data re-sources, security of database, query optimization and database backup


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creating and recovering database from backup. Besides main tool for creating application such as Oracle Forms there is presented PL/SQL language. Topics Architecture of system: Physical and logical structure of database; Different types of files (data files, control files and logfiles); Memory structure and processes. Designing and creating database: Specifying size of data files and ta-blespaces; Data dictionary; Creating tablespaces. Managing of database resources: Defining ORACLE segments, ex-tents and data blocks; Database Auditing Database security: Users, privileges and roles; Profiles Data integrity: Control structures; Database triggers Query optimization: Explaining query plans (Rule-Based i Cost-Based); Hints Creating database backup: database backup; recovering of database DEVELOPER/2000: tools (Forms V4.5, Reports V2.5), PL/SQL lan-guage. Oracle Forms V4.5 Oracle Reports V2.5 Designer/2000: Process Modeler, System Modeller, Reverse Engi-neering

Course load (hours per semester) ID Course Semester L P Lab

ECTS

M2.53 Compiler construction 9 30 2 Lecturer: Przemysław Szmal


The subject is aimed to present chosen problems connected to construction of compilers, transforming source programs written in high-level programming languages into target programs equivalent to them. Many solution used in compilers can be also applied to interpreting programs. It is also related to the construction of other programs such as


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macro-generators, linkers etc, responsible for generating executable programs. To the student who is familiar with principles of lexical and syntactic analysis, we expose problems due to semantic analysis, intermediate code generation, target code generation and code optimization.

Course description

Semantic analysis tasks. Syntax-directed translation, methods of de-scription. Attributes - synthesized, inherited. Parse-time attribute evaluation. S-attributed and L-attributed syntax-directed definitions. Attribute representation in the parse stack. Attribute dependence graphs. Type checking, type equivalence verification. Run-time environments. Memory organization; activation records, procedure calls. Intermediate code, representations. Translating expressions and in-structions. Back-patching technique. Code generation - target machine models; register and memory man-agement; concurrent processing organization. Code optimization: peep-hole optimization, flow-analysis based global optimisation.



M2.45 Distributed computer sys-tems 9 30 30 5

Lecturer: Rafał Cupek


The goal of classes is showing the problems of using and constructing the distributed computer systems in soft real-time and hard real-time applications. The lecture should help configure distributed real-time systems in particular a well selection of subscribers’ types and kinds, select task scheduling, use monitoring and formal system description


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methods. It also concern on useful efficiency and the useful capacity of used computer systems. The lecture is connected with projecting of distributed computer systems, which perform exchanges between sub-scribers in order to make system well efficient and kip required timing constraints. The lecture describes system on model level, and also shows many practical examples.

Course description

The Distributed System and Real Time System: definition and real-time system’s classification: hard and soft real-time systems. Task and timing: timing constraints, periodic tasks: sporadic tasks, clock access, Universal Coordinated Time, time synchronisation Cris-tian’s algorithm, Network Time Protocol, IEEE 1588 protocol, Logi-cal time, logical clock, vector clocks, Real-Time Scheduling Paradigms: task model, „Best Effort” Schedul-ing, Rate Monotonic Analysis. Global state in distributed systems: Snapshot, consistent system state, Chandy-Lamport algorithm, Marzullo: Neiger algorithm, software monitoring, hardware monitoring, hybrid monitoring, process and system level monitoring, debugging approaches with monitoring sup-port. Formal methods: Petri nets: Events and Conditions Nets, Places and Transitions, Individual Marked Nets. TCPN - Timing Constraint Petri Nets, Time aspects in UML, Real-Time Specification for Java.



M2.47 Programming for Windows 9 30 30 6 Lecturer: Sławomir Cicho�ski


The course teaches how to write applications using native Microsoft Windows 32 Application Programming Interface. Students will find out what is the architecture of Windows API, what services are avail-


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able in this system for the programmer and how to use them in own applications.

Course description

The course covers following areas: Win32 basics: Win32 concepts and architecture, event driven operat-ing system, message queue, message handling, window creation, win-dow procedure, Graphic Device Interface, physical and memory de-vice contexts, drawing basics, TrueType fonts and text output basics, bitblit operations, space transformations, printing, dialog boxes, com-mon dialog boxes, windows controls, common controls, user input (mouse and keyboard messages handling), Multi Document Interface, extending window classes (super- and subclassing), custom controls, Advanced Win32: dynamic libraries, windows hooks, multithreaded applications, threads synchronization, Win32 interprocess communi-cation, Dynamic Data Exchange, Win32 services, Win32 object secu-rity, Component Object Model basics Shell programming. basic techniques: shortcuts, file associations; ad-vanced techniques: item identifier lists, shell handlers (context menu, column provider, copy handler), namespace extensions.



M2.50 Stochastic Simulation 9 15 15 2 Lecturer: Andrzej Chydzi�ski

Course description

The main target of Stochastic Simulation classes is to show techniques of random variables and stochastic processes simulation by means of computer. Stochastic simulation is helpful in engineering of all these systems which have stochastic nature and deal with random events. This may be, for instance, computer networks engineering where usu-ally the streams of packets have complicated random structure. This


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may be reliability engineering where reliability of the system depends on the reliabilities of elements and the structure of the system etc. The course is divided into two parts: lectures and laboratory. The lec-tures includes the following topics: Short revision of probability the-ory and stochastic processes. Random number generators. General methods for generating of continuous and discrete distributions. Methods dedicated to particular distributions. Generating of normal distributions. Simulation of some special processes: Markov chain, Poisson process, inhomogeneous Poisson process, Markov-modulated Poisson process, batch Markovian arrival process, Levy jump proc-ess, Brownian motion, fractional Brownian motion, gaussian proc-esses. Simulation of queueing systems. The laboratory is devoted to practical simulation of random variates and processes using C++ programming language and algorithms pre-sented during lectures.



M2.54 DBMS SQL Server 9 15 15 2 Lecturers: Paweł Kasprowski, Katarzyna Har��lak


The aim of the course is to present the mechanisms of database man-agement systems taking as an example the MS SQL Server Course description

The aim of this subject is making students familiar with the ways of configuration, administration and using the modern database servers. Using the Microsoft SQL Server, students get the knowledge about nowadays possibilities given by the database servers and ways of their usage by the system administrators and by the application program-mers.


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The course subject matter is discussion of administration and usable aspects of the Microsoft SQL Server. They include issues like: data-base server installation, creating new databases with the physical allo-cation data analysis, database security mechanism usage against unau-thorized access, monitoring and tuning the server performance and Transact-SQL language basis. Additionally, distributed databases and OLAP technologies are also presented. During the laboratories students have a possibility of practical exercis-ing knowledge and abilities developed during the course. Subject is organized in co-operation with the Microsoft Company and based on original Microsoft SQL Server materials.

automatic control and robotics syllabi

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