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[ 1 ]
B. Tech. (Computer Science & Engineering)
Part – II: Semester – III (EFFECTIVE FROM ACADEMIC SESSION 2006-2007)
Subjects Contact Hrs. Per Week
L & T P
Credits
Theory
1. CS – 2101 : Discrete Mathematical Structures 3 3
2. CS – 2102 : Data Structures 3 3
3. AM –2100A : Mathematics 4 4
4. EC – 2100A : Electronics and Instrumentation 3 3
5. EE – 2100A : Electrical Engineering 3 3
6. EE – 2100B : Electrical Circuits & Systems 3 3
Total of Theory 19 19
Practical
7. CS – 2301 : Data Structures Lab. 3 2
8. EC – 2300A : Electronic Circuits Lab 3 2
9. EE – 2300A : Electrical Engg. Laboratory 3 2
Total of Practical 9 6
TOTAL OF SEMESTER 28 25
[ 2 ]
B. Tech. (Computer Science & Engineering)
Part – II: Semester – IV (EFFECTIVE FROM ACADEMIC SESSION 2006-2007)
Subjects Contact Hrs. Per Week
L & T P
Credits
Theory
1. CS – 2201 : Programming Languages 3 3
2. CS – 2202 : Digital Circuits and Logic Design 3 3
3. CS – 2203 : Computer Organization 3 3
4. CS – 2204 : Design & Analysis of algorithms 3 3
5. AM –2200A : Numerical Computation 4 4
6. MS-2200A Material Science 4 4
Total of Theory 20 20
Practical
7. CS – 2401 : Programming Languages Lab 3 2
8. CS – 2402 : Digital Circuits Lab 3 2
9. CS – 2403 : Software Project Lab 3 2
Total of Practical 9 6
TOTAL OF SEMESTER 29 26
[ 3 ]
B. Tech. (Computer Science & Engineering)
Part – III: Semester – V (EFFECTIVE FROM ACADEMIC SESSION 2007-2008)
Subjects Contact Hrs. Per Week
L & T P
Credits
Theory
1. CS – 3101 : Microprocessors 3 3
2. CS – 3102 : Theory of Computation 3 3
3. CS – 3103 : Computer Graphics 3 3
4. CS – 3104 : Database Systems 3 3
5. CS – 3105 : Computer Architecture 3 3
6. CS – 3106 : Operating Systems 4 4
Total of Theory 19 19
Practical
7. CS – 3301 : Computer Graphics Lab 3 2
8. CS – 3302 : Microprocessor Lab 3 2
9. CS – 3303 : Operating System Lab 3 2
Total of Practical 9 6
TOTAL OF SEMESTER 28 25
[ 4 ]
B. Tech. (Computer Science & Engineering)
Part – III: Semester – VI (EFFECTIVE FROM ACADEMIC SESSION 2007-2008)
Subjects Contact Hrs. Per Week
L & T P
Credits
Theory
1. CS – 3201 : Artificial Intelligence 3 3
2. CS – 3202 : Computer Networks 4 4
3. CS – 3203 : Software Engineering 4 4
4. EE- 3200A : Control Systems 3 3
5. HU : Open Elective (Humanities) 3 3
Total of Theory 17 17
Practical
6. CS – 3401 : Computer Hardware Lab. 3 2
7. CS – 3402 : Computer Networks Lab. 3 2
8. CS – 3403 : Artificial Intelligence Lab. 3 2
9. CS -3404 : Minor Project 3 2
Total of Practical 12 8
TOTAL OF SEMESTER 29 25
[ 5 ]
B. Tech. (Computer Science & Engineering)
Part – IV: Semester – VII (EFFECTIVE FROM ACADEMIC SESSION 2008-2009)
Subjects Contact Hrs. Per Week
L & T P
Credits
Theory
1. CS – 4101 Intelligent Computing Systems 3 3
2. CS- 4102 : Compiler Design 4 4
3. ME –4100A : Industrial Management 4 4
4. Elective – I 3 3
Total of Theory 14 14
Practical
5. CS – 4301 : Seminar/ Group Discussion 3 2
6. CS – 4302 : Practical Training Viva - 2
7. CS – 4303 : Major Project Phase I 3 2
8. CS – 4304 : Intelligent Computing Lab. 3 2
Total of Practical 9 8
TOTAL OF SEMESTER 23 22
[ 6 ]
B. Tech. (Computer Science & Engineering)
Part – IV: Semester – VIII (EFFECTIVE FROM ACADEMIC SESSION 2008-2009)
Subjects Contact Hrs. Per Week
L & T P
Credits
Theory
1. CS – 4201 : Parallel Computing 3 3
2. CS – 4202 : Real Time Systems 4 4
3. Elective – I 3 3
4. Elective – II 3 3
Total of Theory 13 13
Practical
5. CS – 4401 : Parallel Computing Lab 3 2
6. CS – 4402 : Comprehensive Viva-voce - 2
7. CS – 4403 : Major Project Phase II 9 6
Total of Practical 12 10
TOTAL OF SEMESTER 25 23
TOTAL CREDITS OF B. Tech. COURSE = 196
[Including 50 credits for the First Year]
[ 7 ]
B. Tech. (Computer Science & Engg.) LIST OF ELECTIVES (UNDER GRADUATE)
ELECTIVES FOR SEMESTER – VII
Credit
a) CS – 4103 : Neural Networks 3
b) CS – 4104 : Operations Research 3
c) CS – 4105 : Fuzzy Systems 3
d) CS – 4106 : Fault Tolerant Computing 3
e) CS – 4107 : Modeling and Simulation 3
f) CS – 4108 : Combinatorics and Graph Theory 3
g) CS – 4109 : Natural Language Processing. 3
ELECTIVES FOR SEMESTER – VIII
Credit
a) CS – 4203 : Logic & Functional Programming 3
b) CS – 4204 : Machine Vision 3
c) CS – 4205 : Pattern Recognition 3
d) CS – 4206 : Microelectronics and VLSI 3
e) CS – 4207 : Cryptography 3
f) CS – 4208 : Data Compression 3
[ 8 ]
NOTE: The recommended text books are only indicative. The convener of
the course may use the latest text books and Internet resources.
CS – 2101: Discrete Mathematical Structures
Set theory: Basic concept of set theory, relations and ordering, functions,
Cardinality, Partial order, Equivalence relations, Semi-groups. Lattices and
Boolean algebra: Lattices as partial ordered sets, Boolean algebra, Boolean
functions, representation and minimization of Boolean functions, design example
using Boolean algebra.
Graphs and Trees: Basic concept of graph theory, Storage representation and
Manipulation of graphs, Simple precedence grammars. Mathematical logic:
Prepositional calculus, Predicate Calculus and inference theory and application to
theorem proving. Recurrence relations and solutions.
• Discrete Mathematical Structures, Manohar-Trembley, McGraw Hill.
• Graph Theory, Narshim Deo, PHI.
CS – 2102: Data Structures
Basic structures like arrays, stack and queues, Representing stacks and queues
using arrays and pointers.
Recursive definition and processes, Simulating Recursion, Efficiency in
Recursion.
Linked list structures, Files, Dictionaries Sets and Sequences, Garbage collection
and compaction, trees, tree traversals, Huffman Algorithm, Threaded binary trees,
Representing lists as binary trees, Trees and their applications.
Internal sorting techniques, Exchange sort, Selection and tree sorting, Insertion
sorts, Merge and Radix sort.
Basic search techniques, Tree searching and general search trees, symbolic table
structures and hashing techniques.
Graphs, linked representation of graphs, Graph traversals.
• Data Structures using C & C++, A. S. Taneunbaum,
CS – 2201: Programming Languages.
Distinctive techniques in different programming paradigms, semantic and
compilation issues in various languages.
Imperative languages: Block structure, scope rules, parameter passing, constructs
like co routines, tasks etc.
Functional Programming: Functions, recursion, macros, user-defined control
constructs, higher order constructs, types, data abstraction, polymorphism,
semantics, implementation issues.
[ 9 ]
Declarative Programming: Declarative programming, Hom clauses, procedural
interpretation of Hom clauses, SLD – resolution including unification, the logical
variable, implementation issues abstract m/c’s and compiling to abstract m/c’s.
Objected Oriented Programming: Objects and programming with object, classes
and instances, hierarchies and inheritance, encapsulation, semantics of OO
languages and implementation issues.
Other Paradigms: An Introduction to Concurrent Programming – Parallelism in
Hardware, Streams: Implicit Synchronization, Concurrency as Interleaving,
Liveness Properties, Safe Access to Shared Data, Synchronized Access to Shared
Variables.
• Programming Languages, 2nd
ed., Ravi Sethi, Addison Wesley.
CS – 2202: Digital Circuits and Logic Design
Switching devices, logic gates, digital integrated circuits technologies.
Combination Logic- Analysis Procedure, Design Procedure, Study of Different
Combinational Circuits, HDL for Combinational Circuits. Synchronous
Sequential Logic- Sequential Circuits, Flip-Flops, State Reduction and
Assignment. Registers and Counters- Registers, Shift Registers, Ripple Counters,
Synchronous Counters. Memory and Programming Logic- Introduction, Random-
Access Memory, Memory Decoding, Error Detection and Correction. Read-Only
Memory, Programmable Logic Array, Programmable Array Logic. Asynchronous
Sequential Logic- Introduction, Analysis Procedure, Circuits with Latches,
Design Procedure, Race-Free State Assignment, Hazards. Study of Digital
Integrated Circuits- Transistor-Transistor Logic (TTL), Emitter-Coupled Logic
(ECL) etc.
• Digital Design, 3rd ed., M. M. Mano, Pearson Education.
CS – 2203: Computer Organization
Elements of Computers, limitations of Computers. The Evolution of Computers –
Mechanical Era, Electronic Computers, The Later Generations. The VLSI Era –
Integrated Circuits, Processor Architecture, System Architecture. Processor-Level
Components, Processor-Level Design. CPU Organization –Fundamentals.
Data Representation – Basic Formats, Fixed-Point Numbers, Floating-Point
Numbers. Instruction Sets – Instruction Formats, Instruction Types, Programming
Considerations. Floating-Point Arithmetic.
Instruction Pipelines, Pipeline Performance, Superscalar Processing. Memory
Technology – Memory Device Characteristics, Random Access Memories, Serial-
Access Memories. Memory System – Multilevel Memories, Address Translation,
Memory Allocation. Caches – Main Features, Address Mapping, Structure versus
Performance. Introduction to parallel computer models.
• Computer Architecture and Organization, 3rd
ed., J.P. Hayes, McGraw Hill.
CS –2204: Design and Analysis of Algorithms
Algorithms, problems and instances, average and worst case analysis, elementary
operations, Specifying an algorithm, data structures, asymptotic notation,
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Recursion and iteration, recurrence equation, Euclid’s algorithm. Greedy
algorithms- Minimal spanning tree, shortest path, scheduling, and knapsack
problem. Divide and conquer Sorting- Quick sort, Heap sort, Merge sort,
Searching, binary search, changing two section of an array, finding the median,
arithmetic of large integers, exponentiation matrix multiplication, string
processing algorithms, Fast Fourier Transform. Dynamic Programming: Shortest
paths and optimal search trees, Traveling Salesman problem. Graphical
algorithms- Traversing trees, Depth – First and Breadth – First search.
Backtracking- 8 – queens’ problem, sum of subsets, graph coloring, Elementary
idea of Random Number generators and simulation, Problems classes P, NP and
NP – completeness.
• Computer Algorithms, E. Horowitz-S.Sahani, Galgotia Publishing House.
AM – 2100A: Mathematics
Matrices: Cayley-Hamilton theorem, Symmetric, Skew-symmetric orthogonal
matrices, Hermitian matrices, unitary matrices, Eigen values and eigen vectors,
matrices decomposition, generalized inverses of matrices, Matrix norms,
Convergence and perturbation theorem.
Differential Equations: Self-adjoint second order differential equations, Solution
in series, Bessel functions of first and second kinds, Legendre and Hermite
Polynomials, recurrence relations, orthogonality properties, Sturm_Lioville
problem.
Laplace and Fourier transform of elementary functions, periodic functions, step
functions and their derivatives, inversion and convolution theorems, Applications
to simultaneous linear differential equations and second order differential
equations.
Introduction to stochastic processes and queuing theory and their application in
electrical engineering problems.
AM – 2200A: Numerical Computation
Absolute, relative, round off, truncation errors, significant digits, Estimation of
errors, Tabulation of a function, Interpolation: Ordinary differences, differences
operators, E. and Sub tabulation; divided differences, Newton-Coats formula,
Lagrange’s formula, central ordinary least squares, cubic splines, Solution of
algebraic and transcendental equations graphical method, inverse interpolation,
interactive methods, regular falsi Newton-Rapson method, multiple or near
multiple and complex roots, Solution of linear equations, method of elimination
Numbers, ill conditioned systems, Computing the inverse matrix, eigenvalues and
eigenvectors, matrix decomposition, Numerical integration, finite difference
method, Gaussian quadrature, Euler-Maclaurinn series, asymptotic expansions,
solution of differential equations, Solution in series, Picard’s method, methods of
Adams-Bashforth and Mine and Runge-Kutta, Difference equations, differential
and difference equations, numerical solution of difference equations, relaxation
method, solution of partial differential equations by difference.
EE – 2100A: Electrical Engineering
Electrical Circuits:
[ 11 ]
Network Elements: Voltage and current sources, Kirchoff’s voltage and current
law Loop and nodal analysis, superposition theorem, Thevenin’s theorem,
Norton’s theorem, Maximum power transfer theorem.
Sinusoidal steady state analysis: R,L & C elements, power and power factor,
phasor diagram, resonance, Mutual inductance and coefficient of coupling.
Electrical Machines:
Constructional features of static and rotating machines. Statically and dynamically
induced EMF.
Transformer: Principle of working, EMF equation, Equivalent circuit, voltage
regulation and efficiency, O.C., S.C. and direct load test, Autotransformer.
D.C Machines: Constructional features of D.C. Generator and motor, No-Load
characteristics, speed control, Application.
Induction machines: Principle of operation, Constructional details, Torque-Slip
characteristics, starting and speed control.
Synchronous Machines: Construcitonal features, Voltage regulation of Alternator
and its determination by Synchronous Impedance method. Synchronous motor:
Starting, V and inverted V-curves, Applications.
Distribution of Electrical power: Tariff calculation
Electrical Measurement: Introduction to indicating instruments, ammeter,
Voltmeter, Wattmeter, energy meter.
• Electric Machines by Nagrath & Kothari.
• Fundamentals of Electrical Engineering by Vincent Del Toro
• Advanced Electrical Engineering by H.Cotton.
EE-2100B : Electrical Circuits and Systems
Systems and Signals : Systems-classification and their properties, Signals-
mathematical descriptions of deterministic signals, signal specifications.
Network elements and their characterization. Department and independent
sources. Mathematical descriptions of passive elements.
Modelling of physical systems: Models based on known physical laws, analogous
systems. Network topology- Graph theoretical models of electrical networks and
systems. Loop and modal equations. Dual graphs and dual networks.
Loop and modal methods of analysis: Matrix methods and Network theorems.
Circuit analysis by classical method. Natural and force responses.
The Frequency Domain: Fourier analysis: Fourier series representation of periodic
signals, frequency spectrum, Fourier integral and Fourier Transform Analysis
with Fourier transform.
Laplace Transform Methods: Laplace transform. Transform functions. Analysis
by Laplace transform. Convolution integral.
[ 12 ]
Sinusoidal steady state analysis of RLC circuits: Power and power factor. Phasor
method of analysis. Phasor diagrams. Resonant circuits. Three-phase circuits-
balanced and unbalanced, power measurement. Feedback systems, Masson’s
formula and Signal flow graph. State variables and State space analysis.
EC-2100A : Electronics and Instrumentation
Semiconductor diode characteristics, load line, half wave and full wave rectifiers,
filters, power supply, regulators (723, 78xx, 79xx), Amplifying devices (vaccum
tube, BJT, FET), their characteristic amplifying (including types of coupling),
calculations of V. Gain, Impedances, Frequency Response, Feed-Back; High
input impedance, oscillator circuits (RC, LC, and its applications), Filters, V.C.O.
and PLL; TIMER and applications to systems logic gates and basic logic circuits
(SSI, MSI and basic system ICs); transducers load cell, strain gauge, LVDT,
optical shaft encoder, display device, A/D and D/A converters; CRO and
multimeters (A&D). A typical instrumentation system.
MS-2200A : Material Science
The crystalline state : Atomic bonding, Bravais lattices, Miller indices, X-ray
crystallography, structural imperfections, binary phase diagram, microstructure.
Electron theory of solids : Free electron theory of metals, zone and bond theory of
solids, brillouin zones, classification of conductors, semiconductors, hall effect, p-
n junction and transistor.
Mechanical Properties : Elastic and plastic deformations, strength, hardness,
creep, fatigue, and fracture of materials, processing of materials.
Magnetic Materials : Dia-, Para-, Antiferro- and ferri-magnetism, soft and hard
magnetic materials, metallic glasses.
Superconducting materials : Zero resistance and Meisner effect, soft and hard
superconductor, Josephson junction, high Tc-super conductor.
Dielectric materials : Polarisation mechanisms, Behaviour under switching power
frequency and d.c. voltages, piezoelectric and ferroelectric materials and their
applications.
CS – 3101: Microprocessors
The evolution of Microprocessor Technology: microprocessor architecture, details
of 8-bit/16-bit/32-bit/64-bit microprocessors, instruction set, Machine language
instruction formats, Addressing modes of the microprocesser, assembly level
programming, Interrupts and interrupts service routines, Time delay routines,
interfacing memory and I/O devices, interfacing anolog to digital data converters,
Special purpose programmable perioheral devices and their interfacing such as
programmable interrupt controller, the keyboard or display controller, DMA
controller, Floppy disk controller, micro computers and micro controllers, support
chips, microprocessors development tools, microprocessors based system design
and application, Bus structures Multi bus, VME, ISA, EISA, Coprocessor
[ 13 ]
Architectures and programming, PC hardware, Computer bus interfaces – PCI,
VL bus etc.
• Microprocessors Architecture programming with the 8085, 3rd
ed., Gaonkar,
Penram International Publishing.
• Advanced Microprocessors and Peripherals, 1st ed., A. K. Roy-
K.M.Bhurchandi, Tata McGraw Hill.
CS – 3102: Theory of Computation
Mathematical preliminaries, alphabet, strings, languages, states, transitions, finite
automata and regular expressions, pushdown automata and context free languages
and grammars, context sensitive languages and grammars, Chomsky hierarchy-
Turing Machines: Turing hypothesis, Turing computability, no deterministic,
multitape and other versions of Turing machines, Church’s thesis, primitive
recursive functions,
Godelization, recursive functions, recursively enumerable sets and Turing
computability, Universal Turing machines.
Unsolvability: The halting problem, partial solvability, Turing innumerability,
acceptability and decide ability, unsolvable problems about Turing Machines and
recursive functions, Post’s correspondence problem examples, Review of
prepositional and predicate calculus: syntax, satisfiability, validity.
• Introduction to Automata, Formal Lanuages and Computation, Peter Linz,
Narosa Publishing House.
• Mathematical Theory of Computation, Zohar Manna, McGraw Hill.
CS – 3103: Computer Graphics
Introduction and scope of subject, prerequisites, performance of graphics
algorithms, model of computation, fundamental graphic algorithms.
Computational Geometry: Geometric searching, single shot and repetitive mode
queries, vector dominance, polygon inclusion relations.
Vector generator algorithms, Painting Polygons, Picture Transformations,
Windows, View ports and Clipping, Visualization of surfaces, 3-D
Transformations, Hidden surface Elimination, Half Toning, Thresholding, Quad
tree and Octree models/Realism, Shading, Ray-Tracing, approximations to
shading, Textures, Fractal Geometry methods, Graphics Software Standards,
Graphic Oriented Architecture: requirements and case studies at VLSI and
systems levels, Futures Directions: Virtual Reality, GUI and Multimedia.
• Computer Graphics, 2nd
ed., Foley. , Addison Wisley.
• Computer Graphics, Baker-Haren, PHI.
CS – 3104: Database Systems
Introduction to Database, Entity-Relationship Model, Relational algebra,
Relational Model, SQL-Basic structure views, Modification of database, Joined
relations, derived relations, embedded SQL, others features. Integrity Constraints.
[ 14 ]
Relational Database Design- Decomposition, Normalization Using Functional
Dependencies, Normalization Using Multivalued Dependencies, Normalization
Using Join Dependencies, Domain-Key Normal Form, Introduction to Object-
Oriented Database and Object-Relational Database, Storage and File Structure,
Indexing and Hashing.
Query Processing, Transactions, Concurrency Control, Recovery System,
Database System Architectures. Security and integrity standardization.
• Data Base System Concepts, 4th ed., Korth- Silberschatz, McGraw Hill.
CS – 3105: Computer Architecture
Types and classification of architecture, Computer development milestones,
Parallel computers, hypercube, systolic arrays models, Principles of scalable
performance, Processor and memory hierarchy, Bus, Cache and shared memory,
pipelining and super scalar techniques.
Classification of architectures, Array processors, Vector processors, Vectorisation
methods, supercomputers, Cray – cyber, etc.
Multiprocessors: System interconnects, cache coherence and synchronization
mechanisms, Multicomputer generations, multipart memory, routing schemes,
multi vector computers, Simulation of multiprocessors.
Scalable, Multithreaded and Dataflow architectures, design issues, Data flow
machines, Distributed system, CISC vs RISC, RISC processors, super scalar
processors, VLIW architectures.
• Advanced Computer Architecture, Kai Hwang, Tata McGraw Hill.
CS – 3106: Operating Systems
Computer System Structures. Operating System Structure- System Components,
System Calls. Processes- Process Scheduling, Operation on Processes,
Cooperating Processes. Threads. Scheduling- Scheduling Criteria, Scheduling
Algorithms, Multiple-Processor Scheduling. Real-Time Scheduling. Process
Synchronization- The Critical-Section Problem, Semaphores, Classic Problems of
Synchronization, Monitors. Deadlocks- System Model, Deadlock
Characterization, Methods for Handling Deadlock, Deadlock Prevention,
Deadlock Avoidance, Deadlock Detection, Recovery from Deadlock, Starvation.
Memory Management- Swapping, Contiguous Memory Allocation, Paging,
Segmentation, Segmentation with paging. Virtual Memory- Demand Paging, Page
Replacement, Allocation of Frames, thrashing.
File-System Interface and Implementation- File Concept, Directory Structure,
Directory Implementation, Allocation Methods, Free-space Management,
Efficiency and Performance, Recovery. I/O Systems- I/O Hardware, Application
I/O Interface, Kernel I/O Subsystem, Transforming I/O to Hardware Operations,
STREAMS, Performance. Mass Storage Structure- Disk Structure, Disk
Scheduling, Disk Management, Swap-Space Management, RAID Structure, Disk
Attachment, Stable-Storage Implementation, Tertiary-Storage Structure.
Protection and Security. A case study of modern operating systems.
[ 15 ]
• Operating System Concepts, 6th ed., Silberschatz-Galvin-Gagne, John Wiley
& Sons.
• Operating System: A Modern Perspective, 2nd
ed., Garry Nutt, Pearson
Education.
• Operating Systems: A concept based approach, 1st ed., Dharamdhere, Tata
McGraw Hill.
CS – 3201: Artificial Intelligence
Introduction and historical perspective, Hard and Soft AI – disciplines and
applications, Theories of Intelligence, Detecting and Measuring Intelligence,
Knowledge based approach, the prepare-deliberate engineering trade-off,
Procedural v/s Declarative knowledge, Criticism of symbolic AI, Knowledge
representation, desirable properties of KR schemata, Use of predicate calculus in
AI.
Unification and Resolution, Architecture, design and manipulation of semantic
networks, Frame Systems, Property Inheritance, Procedure Attachment,
Conceptual Dependency, Current research areas in knowledge representation,
Introduction to Natural Language, Processing, Syntax-Semantics-Pragmatics-
Discourse analysis hierarchy, Recursive and Augmented – Transition Networks.
Expert Systems, Components, Production rules, Backwards vs Forward reasoning,
Statistical reasoning, certainty factors, measure of belief and disbelief, Meta level
knowledge, Introspection, Knowledge engineering case studies, Heuristic search
of state space, DFS, BFS, UCS, choice of a search algorithm, Admissibility
theorems, search performance metrics, Game playing, Alpha-Beta pruning,
Quiescence search, Killer Move heuristic, AI programming environments.
AI oriented language and architecture – requirements and taxonomy, Case studies.
• Artificial Intelligence: A new synthesis, Nils J Nilsson, Morgan Kaufmann
Publishers.
• Artificial Intelligence, 2nd
ed., Rich, Tata McGraw Hill.
CS – 3202 Computer Networks Introduction – Uses of networks, hardware, software, classification, reference,
models, and examples networks, standardization.
Physical layer – Theoretical basis, guided transmission medium, wireless
transmission, communication satellites, PSTN, mobile telecom system.
Data link layer – Design issues, error detection and correction, protocols. Medium
access control sublayer- channel allocation, multiple access protocols, Ethernet,
wireless LANs, broadband wireless, bluetooth, switching.
Network layer – Routing algorithms, congestion control, QoS, internet working.
Transport layer – UDP, TCP, performance issues, service models, remote
procedure call, real time transport protocol.
Application layer – DNS, E-mail, world wide web, HTTP, multimedia. Network
security- basic concepts.
[ 16 ]
• Computer Networks, 4th ed., A.S. Tanenbaum, PHI.
CS – 3203: Software Engineering
Introduction: Phases in Software development, software development process
models, role of metrics and measurement.
Software Requirement specification (SRS): Role of SRS, problem analysis,
requirement specification, validation of SRS document, metrics, monitoring and
control, Object-Oriented analysis.
Planning a software Project: Cost estimation, project scheduling, staffing and
personnel planning, team structure, software configuration management, quality
assurance plans, monitoring plans, management.
System Design: Objective, principles, module level concepts, coupling and
cohesion, methodology- structured and object oriented, Design specification and
verification, Metrics, Object-Oriented Design.
Detailed Design: Specification, design language, verification, Monitoring and
control.
Coding: Practice, documentation, verification, correctness proving, metrics,
monitoring and control.
Testing: Fundamentals, functional and structural testing, test plans, test case
specifications, test case execution and analysis.
Software reliability models, methods of reliability enhancement.
• Software Engineering: Theory and Practice, 2nd
ed., S. L. Pfleeger, Pearson
Education.
EE-3200A: Control Systems
Feedback principle, examples of open-loop and closed-loop systems, broad
classification of feedback control systems, effects of feedback.
Physical Systems and their Models: Transfer function of typical control-system
devices. Control system representations: Block diagram, Signal flow graphs,
State-variable representation and State-diagram.
Time-Domain Analysis: Servo specifications in time domain, type 0, 1, 2 systems
and error coefficients. Stability: RH Criterion. Root locus techniques.
Frequency-Domain Analysis: Frequency response plots, Nyquist-plot, Nichols
chart, Servo-specifications in frequency-domain, Stability analysis, PID
controllers in frequency domain.
State-Variable analysis: Decomposition of transfer functions, Similarity
transformation, Controllability, State feedback systems.
Digital Control Systems: Digital computer control system applications, Sampled-
data system, the z-transform methods of analysis, state-variable representation
and analysis of discrete-time systems, stability analysis.
[ 17 ]
CS –4101: Intelligent Computing Systems
Genetic Algorithms- SGA, Evolutionary Computing, Evolutionary Programming,
Genetic Programming, Building block hypothesis, Schema Theorem. Choice of
mutation, crossover probability, population size, meta-genetic algorithm.
Performance Evaluation, Parallel Genetic Algorithms. Social Models-Ant Colony
optimization (ACO). ACO for NP-hard problems e.g. traveling salesperson
problem, applications to network routing. Multi-agent Systems- agents and
environments, rationality, simple and model based reflex agents, goal-based,
utility based and learning agents. Mobile agents and their applications.
• Artificial Intelligence: A modern approach, 2nd
ed., Stuart Russell-Novig,
Pearson Education.
• Ant Colony Optimization, M. Dorigo-T. Stutzle, PHI.
CS –4102: Compiler Design
Problem of Compilation i.e. Translation, Analysis-Synthesis Technique for
Language Processing, Natural and Programming Languages, Compiler,
Assembler and Interpreters, passes of a complier/interpreter.
Lexical analysis, Lexical or Tokens Symbol Table, Hashing.
Parser, Formal Grammar and Languages, BNF and Syntax diagram. Notation for
Formal Grammar, Shift Reduce Parser- (SLR, LALR etc.). Precedence Parsing
Techniques, Recursive Descent parsing etc.
Semantic Analysis, Internal Form, Polish Strings, Syntax Trees Quadruples
Triples and Indirect Triples.
Synthesis, Code Optimization and Generation, Run Time Storage Handling, Error
Detection, Correction and Reporting.
• Compiler Design, Aho-Ullman-Sethi, Pearson Education.
CS – 4103: Neural Networks
Fundamental Concepts – Biological Neurons and their Artificial Models, Neural
Processing, Learning and Adaptation, Neural Networks Learning Rules. Single-
Layer Perceptron Classifiers. Feedforward Networks- Delta Learning rule for
Multiperceptron Layer, Generalized Delta Learning Rule, Feedforward Recall and
Error Back-Propagation Training.
Classifying and Expert Layered Networks, Functional Link Networks. Single
Layer Feedback Networks- Basic Concepts of Dynamical Systems, Mathematical
Foundations of Discrete-Time Hopfield Networks. Associative Memories- Basic
Concepts, Linear Associator, Basic Concepts of Recurrent Autoassociative
Memory, Bidirectional Associative Memory, Associative Memory of Spatio-
temporal Patterns.
Matching and Self-Organizing Networks- Hamming Net and MAXNET,
Unsupervised Learning of Clusters, Feature Mapping, Self-Organizing Feature
Maps. Cluster Discovery Network (ARTI). Application of Neural Algorithms and
Systems.
[ 18 ]
Complexity of Learning, Learnability, N-P completeness of the problems of
learning, Generalizibility, Vapnik- Chervonenkis (VC) dimension, space
complexity of N.N.
• Introduction to Artificial Neural Systems, J. M. Zurada, Jaico Publishing
House.
• Neural Network Fundamental, N. K. Bose-P. Liang, McGraw Hill.
• Neuro Computers: Optimization Based Learning, K. K. Shukla, Narosa
Publishing House.
CS – 4104: Operations Research
Linear programming, extreme point solutions, simplex method, computational
procedures, duality problems, degeneracy, Revised simplex, sensitivity analysis,
nonlinear programming, dynamic programming, integer programming,
combinational optimization, transportation and assignment problems, networks
flows, simple inventory models, Queuing Models and Networks, global
optimization techniques and their applications.
CS – 4105: Fuzzy Systems
Introduction to Fuzzy Sets: Fuzzy Sets characterizations, Algorithms and
Extension, Fuzzy Sets in the development of the cognitive perspective: Fuzzy
Controllers: Preliminaries and Basic Construction, Fuzzy Relational Equation,
Design Aspects of Fuzzy Controllers, Theoretical and Conceptual Developments
in the Construction of Fuzzy Controllers: Relational Neural Networks,
Developments of Fuzzy Controllers – Fuzzy Neural Network Approach,
Identification of Fuzzy Models, System Analysis in Fuzzy: Relational Models,
Fuzzy Classifiers, Fuzzy Hardware/Software.
• Fuzzy set Theory and Its Application, 2nd
ed., H.J. ZimmerMann, Allied
Publishers Limited.
CS – 4106: Fault Tolerant Computing
Models of Computers with faults, Classification of faults and failures, Fault
tolerance by massive redundancy, Fault detection, recovery and reconfiguration,
modeling, Case study of representative fault tolerant computing systems,
Software reliability, N-modular redundancy, N-version Programming, Fault
tolerance in concurrent software, Gracefully degrading systems, performability,
Architectural design of fault tolerant computing systems.
CS – 4107: Modeling and Simulation
Selected illustrative examples of simulation application Models: Structural,
Process, Continuous, Discrete, Deterministic, Random, Input/Output, static,
dynamic multilevel.
Simulation: Analog/Digital/Hybrid techniques, verification and validation.
Data Modeling and Analysis: Population parameters, hypotheses testing,
confidence intervals, goodness of fit estimating transient, Steady state
characteristics, variance reduction.
[ 19 ]
Simulation Process: Problem formulating, model building, data acquisition, model
translation, verification, validation, strategic and tactical planning,
experimentation analysis of results, implementation and documentation,
Simulation Language.
CS – 4108: Combinatorics and Graph Theory
General counting methods for arrangements and selections, Generating functions,
Partitions of integers, recurrence relations, solution of linear recurrence relations,
divide and conquer relations, recursive programming, arrangements and
derangements, Burnside lemma, Polya’s enumeration formula, principles of
inclusion and exclusion.
Introduction, paths, connectedness, paths, circuits, planarity, domination,
coloring, covering and partitioning, chromatic number, cut sets, isomorphism,
matrix representation, matching in bipartite graphs, graph theoretic algorithms.
• Applied Combinatorices, Allen Tucker, Willey & Co.
• Graph Theory, Narshim Deo, PHI.
CS – 4109 :Natural Language Processing
Introduction to NLP, Language Structure and Language Analyzer- Overview of
language, requirement of computational grammar. Words and their Analyzer,
Morphological analysis, Local word grouping. Paninian Grammar- The semantic
model, Free word order and Vikhakti, Paninian theory, Active Passive, Central.
Paninian Parser- Core Parser, Constraint Parser, Preference over pares, Lakshan
Charts sense disambiguation. Machine Translation.
Lexical Functional Grammar, LFG and Indian Languages, Tree Adjoining
Grammar, Comparing TAG with PG Government and Binding, Comparing GB
with PG.
• Natural Processing: A Paninian Perspective, A. Bharti-V. Chaitanya-R.
Sangal, PH.I.
CS –4201: Parallel Computing
Review of multiprocessor and distributed systems, Conditions of parallelism,
program partitioning and program flow mechanisms.
Parallel Models: Shared memory model, message memory model, data parallel
model, object-oriented model, functional and logic models.
Parallel Algorithms: Cost, Efficiency, PRAM algorithms, Mesh algorithms,
hypercube algorithms, combinational circuit algorithms.
Parallel languages and compilers: Language features for parallelism, parallel
language constructs, optimizing compilers for parallelism, dependency analysis,
code optimization and scheduling, loop parallelization and pipelining.
Parallel program development: Parallel programming environments,
synchronization and multiprocessing modes, shared variable program structures,
message passing, program development, mapping programs onto, multi
computers.
[ 20 ]
Multiprocessor UNIX (design goals)- Master slave and multithreaded Unix, multi
computer Unix extension, Mach/OS kernel architecture, OSF/1 architecture and
programming environment.
• Parallel Computing: Theory and Practice, 2nd
ed., M. J. Quinn, Tata McGraw
Hill.
CS – 4202: Real-Time Systems
Real Time System - Issues in Real-Time Computing, Structure of a Real-Time
Systems, Characterizing Real-Time System and Tasks. Task Assignment and
Scheduling- Classical Uniprocessor Scheduling Algorithms, Uniprocessor
Scheduling of IRIS Tasks, Fault-Tolerant Scheduling. Programming Language
and Tools- Desired Language Characteristics, Data Typing, Control Structure,
Facilitating Hierarchical Decomposition, Packages, Run-Time Error (Exception)
Handling etc.
Real-Time Databases – Basic Definition, Real-Time vs. General-Purpose
Databases, Main Memory Databases, Transaction Priorities, Transaction Aborts,
Concurrency Control Issues, Disk Scheduling Algorithms. Databases for Hard
Real-Time Systems. Real-Time Communication – Network Topologies,
Protocols. Fault-Tolerance Techniques – Causes, Types, Detection, Fault and
Error Containment, Redundancy, Data Diversity, Reversal Checks, Malicious or
Byzantine Failures, Integrated Failure Handling. Reliability Evaluation
Techniques. Clock Synchronization-Impact of Faults, Fault-Tolerant
Synchronization in Hardware, Synchronization in Software.
• Real Time Systems, Krishna- Shin, Tata McGraw Hill.
CS – 4203: Logic and Functional Programming
Functional Programming: Introduction, Lambda, Calculus, Translating high-level
functional language into the lambda calculus, structured types, semantics of
pattern matching and efficient compilation, list comprehension, Polymorphic type
checking, Graph reduction of lambda expression, lazy evaluation, Super
combinators, SK combinators, G-code, strictness analysis, SASL, MIRANDA.
Logic Programming: Logic and Reasoning, Logic programs, Implementation of
Logic programs, Applications, PROLOG, PARLOG, LISP.
CS – 4204: Machine Vision.
Introduction, Recognition Methodology, Thresholding and Segmentation, Region
Analysis, Mathematics of Morphology, Neighborhood Operators, Labeling, Facet
Model, Texture, Feature Extraction, Hough Transform, Uniform error estimation,
Case Studies, Early Visual Processing: Image Representation, The Raw Primal
Sketch, Grouping Processes. Full Primal sketch, Intermediate processing,
Computational Approach to stereopss, Visual motion computation. The 2.5
Sketch, Parallel Algorithms, Pyramidal Architecture of vision.
• Computer and Robot Vision Vol. 1, R. M. Haralick-L.G. Shapiro, Addison-
Wesley Publishing Company.
CS – 4205: Pattern Recognition
[ 21 ]
Preliminary concepts and preprocessing phases, coding, normalization, filtering,
linear prediction, Feature extra action and representation thresholding, contours,
regions, textures, template, matching, Data structure for pattern recognition,
statistical patter recognition, clustering Technique and application, Case studies.
CS – 4206: Microelectronics and VLSI
Introduction to VLSI technology complexity of design and need for automation.
Placement and routing. PLA’s folding and partitioning, Physical layout design.
Design rule checking, Simulation, testing and design and testability. Reliability
and yield analysis.
CS – 4207: Cryptography
Introduction, symmetric cryptography, one-way hash functions, digital signatures,
pseudorandom sequence generation.
Intermediate, advanced and esoteric protocols, disclosers of secrets, zero –
knowledge proofs, digital certified mail, secure multi-party computation.
Key management, generating and storing keys, key length, lifetime of keys.
Algorithm types and models, self-synchronizing stream ciphers, block Vs stream
ciphers.
DES, AES, RC2, IDEA, RC5, CRAB, RSA, COMSET, PGP, legal issues.
CS – 4208: Data Compression
Mathematical Preliminaries – Information theory, average information content,
Entropy. Source models-Physical, probabilistic, Markov, Composite models.
Uniquely decodable codes.
Huffman coding, arithmetic coding, Dictionary techniques, predictive coding.
JPEG-LS, CCITT group 3, 4 recommendations, comparison of MH, MR, MMR,
JBIG.
Lossy coding – distortion criteria, Human visual system, conditional entropy,
average mutual information, differential entropy.
Scalar and vector quantization, differential encoding, transforms, sub-band and
wavelets, video compression techniques and standards. Performance metrics for
compression algorithms.
• Introduction to Data Compression, 2nd
ed., Khalid Sayood, Morgan Kaufmann
publishers.
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