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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

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Part – II: Semester – IV (EFFECTIVE FROM ACADEMIC SESSION 2006-2007)


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


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



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Part – III: Semester – V (EFFECTIVE FROM ACADEMIC SESSION 2007-2008)


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


Practical

7. CS – 3301 : Computer Graphics Lab 3 2

8. CS – 3302 : Microprocessor Lab 3 2

9. CS – 3303 : Operating System Lab 3 2



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Part – III: Semester – VI (EFFECTIVE FROM ACADEMIC SESSION 2007-2008)


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


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



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Part – IV: Semester – VII (EFFECTIVE FROM ACADEMIC SESSION 2008-2009)


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


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



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Part – IV: Semester – VIII (EFFECTIVE FROM ACADEMIC SESSION 2008-2009)


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


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 CREDITS OF B. Tech. COURSE = 196

[Including 50 credits for the First Year]

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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

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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.

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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:

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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.

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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

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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.

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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.

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• 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.

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• 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.

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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.

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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.

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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

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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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