Course Structure for M.Sc. (Computer Science)
701. Theory of Computation 4 1 - 25 75 100
702. Advanced Data Base Management System 4 1 - 25 75 100
703. Artificial Intelligence 4 1 - 25 75 100
704. Laboratory – IV
(a) Practical on Advanced DBMS - - 6 13 37 50
(b) Practical on Artificial Intelligence - - 6 12 38 50
801. Software Engineering 4 1 - 25 75 100
802. Principles of Computer Design 4 1 - 25 75 100
803. Modelling and Simulation 4 1 - 25 75 100
804. Laboratory – V
(a) Practical on Computer Design - - 6 13 37 50
(b) Practical on Modeling & Simulation - - 6 12 38 50
901. Advanced Computer Architecture 4 1 - 25 75 100
902. Operating Research 4 1 - 25 75 100
903. Parallel & Distributed Computing 4 1 - 25 25 100
904. Laboratory – VI
(a) Practical on Operations Research - - 6 13 37 50
(b) Practical on Parallel & D. Computing - - 6 12 38 50
1001. Elective** 4 1 - 25 75 100
1002. Project - - 30 75 225 300
1. Digital Image Processing
2. Natural Language Processing
3. Fuzzy Set Theory and Application
4. Neural Networks and Applications
5. Internet Technologies and Applications
L: Lecturer Hrs/Week T: Tutorial P: Practical Hrs/Week
S: Sessional Marks E: End Semester Marks TM: Total Marks
Total Marks / Semester – 400
701. Theory of Computation
Deterministic and Nondeterministic Finite Automata (DFA and EFA).
Equivalence of DFA and NFA. Properties of the languages Accepted by Finite Automata
Recursive Definitions, Regular Expression, Transition Graphs, Kleen’s Theorem, Regular and Non-regular language.
Context-free Grammar, Regular Language and context free language, Chomsky’s Normal Form, Pushdown Automata, Properties of Context Free Languages, Determinism and Parsing.
Turing machines (TM) : Computing with TM, Post machines, Winsky’s theorem, Extension of the TM, Chomsky’s Hierarchy.
Primitive and n-Recursive Function, Church’s thesis.
The Halting problem, Unsolvability, Computational Complexity.
1. D.I.A Cohen : Introduction To Computer Theory (J.Wiley).
2. H.R.Lewis & C.H. Papadimitrion : Elements of The Theory of Computation (P.H.I)
3. J.E.Hoperolt & J.D.Ullman : Introduction To Automata Theory, Language and Computation (P.H.I)
4. J.Caroll & D.Long : Theory of Finite Autamata
5. M.Davis & Weyukur : Computability, Complexity and Languages.
6. M. Machtey & F.R. Young : Introduction To Gencel Theory of Algorithms.
702. Advanced Data Base Management System
Object Oriented Database: Persistent Programming Language, Object identity and its implementation, Clustering Indexing, Client Server Object Bases Coherence.
Parallel database: Parallel Architectures, Performance measures, shared nothing/shared disk/shared memory based architectures, Data partitioning, Intraoperator parallelism, Pipelining, Scheduling, Load balancing, query optimization with Volcano as a case study.
Distributed Database : Query processing, semi-joins, quey optimization, Concurrency
Control Heterogeneity issues.
Advanced Transaction Models : Savepoints, Sagas, Nested Transactions, Multilevel Transactions, recursive query processing : Top-down and bottom-up evaluation, Magic optimization.
Recovery : Multi-level recovery, Shared disk system, Distributed system 2PC, 3PC, replication and hot spares.
Recursive query processing : Top-down and bottom-up evaluation, Magic optimization.
1. DATABASE SYSTEM CONCEPTS : KORTH AND SILBERSCHTZ (TATA McGRAW HILL)
2. FUNDAMENTALS OF DATABASE SYSTEM : R. ELMASRI AND S. NAVATHE (BENJAMIN CUMMINGS)
3. DATABASE TRANSACTION MODELS FOR ADVANCED APPLICATIONS : AHMED K. ELMAGARMID (MORGAN KAUFMANN)
4. TRANSACTION PROCESSING, CONCEPTS AND TECHNIQUES : J.GRAY AND A. REUTER
5. INTRODUCTION TO OBJECT ORIENTED DATABASE : WON KIM (MIT PRESS)
6. READINGS IN OBJECT ORIENTED DATABASE SYSTEM : S.ZDONIK AND D. MAIER (MORGAN KAUFFMAN)
7. READING IN DATABASE SYSTEMS : m. STONEBRAKER
8. DISTRIBUTED DATABASE PRINCIPLES AND SYSTEM : S. CERI AND G. PELAGGATI (McGRAW HILL)
703. Artificial Intelligence
Definition, Short History of Artificial Intelligence (AI), Brief Discussion of Major Topics (Expert System, Natural Language Processing, Speech and Pattern Recognition etc.) of AI. Problem Definition as a State Space Search, Production System, Control Strategies, Problem Characteristics.
Forward Versus Backward Reasoning, Matching, Indexing, Search Techniques, Depth-First and Breadth-First Search Technique Best First Search, A*, AO* algorithms Adding Heuristics, Hill-Climbing, Search Technique, Problem Reduction, Constraint Satisfaction, Game Playing.
Knowledge Representation in predicate and Prepositional Logic, Resoulation in Predicate & Prepositional Logic, Deduction and theorem Proving, Question Answering, Structured Representation of knowledge declarative representation semantic networks conceptual dependencies frames and scripts procedural representation.
Overview of Expert System, Design of Rural-Based Expert System, Selecting a problem for expert system development. The knowledge Engineering Process, Conceptual models and their role in Knowledge acquisition.
AI language & their important characteristics, Overview of LISP and PROLOG, Computer Architectures for AI Application, LISP Machines & Parallel Machines.
Implementation in LISP or PROLOG.
1. E.Rich : Artificial Intelligence (Mc Graw)
2. P.H. Winston & B.P.Horn : Lisp (A.Wesley)
3. E. Charniak & D.Mc Dermott : Introduction to Artificial Intelligence (A.Wesley)
4. P.H. Winston : Articial Intelligence (A.Wesley)
5. S.Garavaglia : PROLOG Programming Techniques and Application (Harper)
6. A.Barr & E.A.Feigenbaum : The Handbook of Artificial Intelligence 3 Vols. (Los Altos)
703. Artificial Intelligence
Definition, Short History of Artificial Intelligence (AI), Brief Discussion of Major Topics (Export System, Natural Language Processing, Processing, Speech and Pattern Recognition etc.) of AI. Problem Definition as a state Space Search, Production System, Control Strategies, Problem Characteristics.
Forward Versus. Backward Reasoning, Matching, Indexing, Search Technique, Depth- First and Breath-First Search Techniques, Best First Search, A*, AO* algorithms Adding Heuristics, Hill-Climbing, Search Technique, Problem Reduction, Constrain Satisfaction, Game Playing.
Knowledge Representation in predicate and Prepositional Logic, Resolution in Predicate & Prepositional Logic, Deduction and theorem Proving, Question Answering, structured Representation of knowledge declarative representation semantic networks conceptual dependencies frames and scripts procedural representation.
Overview of Expert System, design of Rule-Based Expert Systems, Selecting a problem for expert system development. The knowledge Engineering Process, Conceptual models and their role in Knowledge acquisition.
AI languages & their important characteristics, overview of LISP and PROLOG, Computer Architectures for AI Applications. LISP Machines & Parallel Machines.
Implementation in LISP or PROLOG.
1. E.Rich : Artificial Intelligence (Mc Graw)
2. P.H.Winston & B.K.P. Horn : Lisp (A.Wesley)
3. E.Charniak & D.Mc Dermott : Introduction to Artificial Intelligence (A.Wesley)
4. P.H.Winston : Articial Intelligence (A.Wesley)
5. S.Garavaglia : PROLOG Programming Techniques and Application (Harper)
6. A.Barr & E.A.Feigenbaum : The Handbook of Artificial Intelligence 3 Vols. (Los Altos)
VIII – Semester
801. Software Engineering
Importance of software, Characteristics, Components, Applications of Software, Software Myths. Definition the Classic Life Cycle, Prototyping, The Spiral Model, Fourth- Generation Techniques. Planning and Management of software Project : People, problem and process, measures, matrices and indicators, matrices for software quality, scooping, software project estimation, make-buy decision, software acquisition.
Software risks : Identification, Projection assessment, monitoring, Project scheduling and tracking tasks/work breakdown structures, timeline chart, project plan, CASE tools. Requirement analysis : Communication techniques. FAST, quality development, analysis principles, modeling, partitioning, prototyping, specifications, SRS and SRS reviews, analysis models : data modeling, functional modeling and information flow, Data flow diagrams, extensions to real-time systems, behavioral models, machanics of structured analysis, ER diagrams, control modeling, data dictionary CASE tools.
Design Fundamentals : Software design and software design process, principles and concepts, abstraction, refinement and modularity, software architecture, control hierarchy, partitioning, data structure, information hiding, effective modular design, cohesion, coupling, design module, design document.
Design Method : Architectural design and design process, transform and transaction flow, design steps, Interface design, procedural design, graphical and tabular design notations.
Software testing and testing strategies : Software testing fundamentals, test case design, white-box, black-box testing, control structure testing, strategic approach to testing, strategic issues, unit testing, integrated testing, validation testing, system testing.
Software quality concepts, Software quality assurance (SQA) and approaches, Software Reliability, SQA plan, ISO 9000 and SEI standards for software, software configuration management (SCM), base lines, scan process, version control, change control, SCM audits.
1. Roger Pressman : Software Engineering, A Practitioner’s Approach, 4th Ed., Tata Mgraw Hill pub.
2. P.S.Pressman : Software engineering (Mc Graw Hill)
3. Pankaj Jalote : An Integrated Approach of Software Engineering (Galgotia)
4. M.Shooman : Software engineering (Mc Graw Hill)
802. Compiler Design
Overview of process, some compiler structures. Regular expression, finite automata and Lexical Analysis, Syntax tress, ambiguity, context free grammar & derivation of parse trees, basic-parsing techniques, deduction.
Syntax – Direction Translation : Top-down and bottom-up parsing operator precedence parsing, LR parsers, syntax direction definition, translation schemes, L-attributed & S-attributed definition.
Symbol Tables : The contents of a symbol table, Data structures for symbol table (ST), design of ST, ST for block structured languages.
Run-time storage administration : Storage allocation strategies, static dynamic & heap memory allocation, memory allocation in block structured languages, memory allocation in recursion, memory allocation in FORTRAN.
Code Generation: Object programs, Problems in code generation, a machine model, A machine model. A simple code generator, Register allocation and assignment, Peephole optimization.
1. D.M.Dhamdhere : Complier Construction – principles & practice (McMillan)
2. A.V.Aho, R.Sethi & J.D.Ullman : compiler-principles, techniques & tools (A.Wesley)
3. J.Trembley & P.G.Sorrenson : the theory and practice of compiler writing (McGraw)
4. W.A.Barrett et al : compiler construction theory & practice (Galgotia)
5. D.Gries : compiler construction for digital computer (JW)
6. A.V.Aho and J.D.Ullman : Principles of Computer Design, (Narosa Publishing House)
803. Modelling and Simulation
System models and role of simulation: Basic concept and nomenclature, Type of system – deterministic, stochastic, continuous and discrete system, System simulation – uses of simulation and its limitations, steps in simulation studies, Random variate generation for Uniform, Exponential, Normal and Poisson distributions, Sampling and estimation, Maximum ;likelihood estimation, Confidence interval estimation.
Discrete Event Simulation : Representation of time, Approaches to discrete event simulation, Queuing models – single and multiserver queues, steady state behavior of queues, network of queues, Inventory system simulation, Programming languages for discrete event system simulation – GPSS,SIMSCRIPT (brief overview).
Modeling and performance evaluation of computer system : Behavioral, data flow and structure modeling, overview of hardware modeling and simulation using VHDL, VHDL description for design reuse, test generation and fault simulation for behavioral model, Single server Centre models, central server models of interactive systems, use of VHDL in front-end and back-end system development, Evaluation of multiprocessor systems, workload characterization & benchmarks.
Continuous system simulation : Continuous system models- open and closed loop system, Models decribed by differential equations, System dynamics, Growth and decay models, Systems dynamics diagram, Simulation of aircraft models, Biological and sociological system simulation, Simulation languages overview – CSMP.
Virtual reality modeling : Overview of Virtual reality modeling language VRML 2.0, creating dynamic worlds, Integrating Java scripts with VRML, Verification and validation of simulation models- Goals of model verification and validation, Input data analysis, Output analysis, Sensitivity analysis, Hypothesis testing, Performance measures and their estimation.
1. J.E.Banks and J.S.Carson II “ Discrete System Simulation “, Prentice Hall, Englewood Cliff, NJ.
2. G.Gordon “System Simulation, Prentice Hall, Inc., Englewood Cliffs, NJ.
3. D.Ferrari “Computer System Performance Evaluation, Prentice Hall, NJ”.
4. J.Bhasker “ Computer System Performance Evaluation, Prentice Hall, NJ.
5. Glenn Vanderburg et. Al. “Tricks of the Java Programming Gurus, Sams. Net Publishing, 1996.
6. Narsing Deo “System Simulation with Digital Computer” PHI pub.
901. Advanced Computer Architecture
Introduction to parallel processing, parallel computer Structures, pipeline and Array Computers, Multiprocessor System, Architectural Classification Scheme.
Principles of pipeline and Vector-Processing, Multification and Array Pipelines, Design of Pipelined Processors, Data buffering and busing System, Vector Processing Requirements, Pipeline Computers and Vectrization Methods, Architecture of Typical Vector Processors, Vectorization and Optimization Methods.
Structures and Algorithms for Array Processors, SIMD Array Processors, SIMD Interconnection Networks, Typical Parallel Processors, Multiprocessor Architecture, Loosely and Tightly coupled Multiprocessor , Interconnection Networks.
Data Flow Computer Architecture, Reduced Instruction Set Computer and Architecture Characteristics.
1. K.Hwang and F.A.Briggs : Computer Architecture and Parallel Processing (McGraw Hill)
2. D.P.Bertsckas and J.N.Tsltsiklis : Parallel and Distrubuted Computation (PHI)
3. M.S.Stone : Introduction to Computer Architecture (Galgotia)
4. R.W.Hockney and C.R.Jesshope : Parallel Computer (Adam-Hilger)
5. K.Hwang : Super Computer Design and Application (Computer Society Press)
902. Parallel & Distributed Computing
Introduction, Minsky’s Conjecture, Amdhl’s
Law, Gustalson’s Law, Tree, Dismond Network, Mesh, Linear arrar, Ring, Star, Hypercube, Chordal ring, Cube- connected cycles, perfect shuffle network, ILLIAC IV, Torus, PM 21, Butterfly, Mesh of tree, Pyramid, Generalized Hyperbus, Twisted cube, Folded Hypercube, Incomplete Hypercube, Enhanced Incomplete Hypercube, Cross Connection Cube, Banyan Hypercube.
Non blocking Networks : CLOS, Rearrangable Benes Network, Blocking Networks: Baseline, Omega, Flip (Cube). PRAM, CRCW, CREW, EREW, Simulating CRCW on CREW & EREW. Boolean Circuit Model, Theorem 1* (Pipepenger and Fisher). Theorem 2** (Borodin). NCK Problems, P – Complete problems, PRAM algorithms : List Ranking, Parallel Prefix on a list, Finding Roots of trees in a Forest, Maximum of an Array, etc.* Relating sequential Time with Parallel Space.** Related Sequential Space with Parallel time. Addition on Tree, Cube, Mesh, Linear array, PSN, etc. Matrix multiplication on Mesh, Cube, Tours etc.
Parallel Sorting : Odd – Even transportation sort on Linear Array, Merge Splitting sorting, Theorem of Odd-Even Merging, Zero- One Principle, Batchers networ, Bitonic sorting on PSN, Mesh, Tree, Hypercube, Time and comparotor requirement for odd-even and Bitonic sorting.
Fourier transforms on Butterfly, Cube, PSN etc. Associative processing : Examples systems like STARAN , PEPE, Associative algorithms such as Pattern Matching, Finding maximum and minimum elements, Not smaller-then search, Summation of Vector Components, etc. LAN, WAN, NOS, DOS, Distributed File Servers, Distributed Real Time System, Client Server Computing.
Procedure calls mechanism and message passing – example DOS System such as ACCENT O.S. and SODS/O.S. File server and example systems such as Xerox, Cambridge, Electronic Mail Server and example system such as Grapevine.
Distributed Database, Concurrency Control in Distributed Database, etc.
1. Hwang and Brigs : Computer Architecture and Parallel processing (PHI).
2. Crichlow : Introduction to Distributed and Parallel Computing.
3. M.J.Quinn : Designing of efficient algorithms for Parallel Computers (McGraw).
4. V.Rajaraman : Elements of Parallel Computing (PHI).
5. Joseph Ja Ja : Introduction to Parallel Algorithms.
6. S.G. Akl : The Design and Analysis of Parallel Algorithms. Prentic Hall, NJ 1989
7. S.G. Akl “ Parallel Sorting Algorithms “, Academic Press 1985
8. R.H.Perrott, “Parallel Programming”, Addisson – Wesley 1987
9. Kai Hwang, “Advanced Computer Architecture – Parallelism, Scalability, Programmability”, McGraw Hill Inc. 1993.
10. Michael J. Quinn, “Parallel Computing – Theory and Practice (second edition) McGraw Hill 1994
903. Operations Research
Introduction, convexity and related results, Linear programming problem, Solution by Graphical and Simplex method. Theory of simplex method, optimality condition, Duality, Fundamental Theorem of duality.
Study of transportation Problem – Method for finding initial solutions (North-westcorner method, Last cost method, Vogels Approximation Method), Modi method for optimum solution, Assignment problems- Mathematical formulation and solutions of assignment problems, Hurgerian method, Variations of Assignment problems, travelling salesman problem.
Revised Simplex method, Sensitivity Analysis, Integer programming formulation- types of integer programming, concepts of a cutting plane, Gomory’s all integer cutting plane method, Gomory’s mixed integer cutting plane method, Branch and bound technique.
Introduction to game theory, Maximum-minimum Principle, games without saddlepoint, reduction to LPP< Networks Scheduling by PERT and CPM, Critical path analysis. Resource Analysis in Network Scheduling, Project cost, Time cost Optimization algorithm, Probability in PERT Analysis.
1. J.Mehdi : Stochstic Process, Wiley Eastern.
2. H.M. Wagner : Principles of Operations Research, PHI
3. H.A.Taha : Operations Research, PHI.
4. W.Gass : Linear programming
5. J.K.Sharma : Operation Research, theory and applications, Mcmillan.
6. W Feller : An introduction to Probability theory & its applications, Wiley Eastern.
7. M.R. Spiegel : Probablity and statistics, Schaum series.
8. C.W.Chrchman & EL Arnchoff : Introduction to Operation Research, Wiley.
9. E.Gillett : Introduction to Operations Research, Tata McGraw Hill
10. D.Gros & C M Harris : Fundamentals of Queuing theory, Wiley.
(1) Digital Image Processing
Levels of Computer Vision, Role of Computer, Relationship with Human Vision System. Image Formation : Image Capture, Imaging Geometry, Image Functions, Properties- Spatial & Color, Perspective – Projective Transform, Camera Calibration, Radiometric Image Formation – Bi-directional Reflectance Distribution Function.
Early Processing : Image Sampling & Digitization, Image Transforms (Fourier, Walsh-Hadamard, Discrete Cosine, Karhunen-Loeve), Image Filtering (Linear and Nonlinear Operators, Lowpass, Highpass, Median Fultering), Gray Level to Binary Conversion (Thresholding, Halftoning), Histogram Equalization, Image Compression.
Image Segmentation : Edge Based Approaches, Texrural Segmentation, Use of Hough Transform, Geometrical feature Extraction, Morphological Method (Minkowski’s Operators), Pyramidal Processing.
Image Motion : Image Sequence Analysis, Optical Flow, Spatio-Temporal Relationship, Dynamic Image Analysis.
Three-Dimensional Vision : Shape from shading, Shape from Texture, Structure from Motion, Binocular stereo (Epipolor Geometry, Corresponding Problem, Surface Extraction).
Object recognition : Pattern Recognition (Nearest Neighborhood Technique, Bayes Theory), Unsupervised Learning and Clustering, 2-D Object Recognition, Polyhedral Surfaces (Understanding line Drawing), 3-D Object Recognition.
1. R.Schalkoff, “Digital Image Processing and Computer Vision”, Wiley.
2. D.H.Ballard and C.M.Brown, “Computer Vision”, Prentice Hall.
3. R.C.Gonzalex and P.Wintex, “Digital Image Processing”, Addision-Wisley.
4. A.K.Jain, “Fundamentals of Digital Image Processing”, Prentice Hall, India.
5. J.M.Brady, Ed.”Computer Vision”, Noth Holland 1984
6. W.K.Pratt, “Digital Image Processing”, John Wielly & Sons 1978
7. J.Serra, “Image Analysis and Mathematical Morphology”, Academic Press 1982.
(2). Natural Language Processing
Introduction to NLP : Some example application, Achievements and brief history, Open problems, Major Goals.
Introduction to Language Structure and Language Analyzer : Introduction to Language Structure, Overview of Language Analyzer Requirement of Computational Grammars.
Preprocessor : Objectives of Processor, Analyzing a text, Discourse Language, Punctuation’s, Abberviations, names, special characters, Need for human Preprocessor.
Words and their Analyzer : Introduction, Why Morphological Analysis, Morphological Generation using paradigms, Morphological Analysis using Paradigms, Speedup Morphological Analysis by compilation, Morphological Analyzer – Some Additional Issues.
Rule Base : Sentences and their analysis, Why Rule Base, Application in Rule Base, Verb Groups, Noun Group, Strategy for Grammar Development, Semantics in stages.
Machine Translation : Introduction, Problems of Machine Translation, Is Machine Translation?, Brief History, Possible Approaches, ANGLABHARTI and its importance.
1. Natural Language Processing – Akshar Bharati, Vineet Chaitanya, Rajeev Sangal (PHI)
2. Abhayankar, K.V. and V.P. Limaye, Vakyapadiya of Bhartrhari Vol.2, Sanskrit and Parkrit Series, University of Poona, Pune.
3. Sangal, Rajeev, Programming Paradigms in LISP, McGraw Hill, New York.
4. Renu Jain, R.M.K. Sinha, Natural Language Processing.
5. Sangal, Rajeev, Vineet Chaitanya and Harish Karnick, “An Approach to Machine Translation in Indian Languages”, Proc. Of Indo – US Workshop on System and Signal Processing, IISc, Bangalore.
(3). Fuzzy Set Theory and Application :
Introduction, Basic concepts on fuzzy sets, Fuzzy sets versus crisp sets, Properties of alpha-cuts, Representation of fuzzy sets, Extension principle, Fuzzy arithmetic – Fuzzy numbers, Arithmetic operations on fuzzy numbers.
Operation on fuzzy sets, Fuzzy union, intersection and complement, combinations of operations, Fuzzy relations, Projections & cylindric extentions, Binary fuzzy relations, Fuzzy equivalance and compatibility relations, Fuzzy ordering relations, Fuzzy morphism.
Fuzzy measures, Belief and possibility measures, Evidence theory, Possibility theory versus Probability theory, Fuzzt logic, Multivalued logic, Fuzzy propositions, Fuzzy qualifiers.
Approximate reasoning – Fuzzy expert system (an overview), Fuzzy implications, Selection of fuzzy implication, Multiconditional approximate reasoning, Fuzzy system (general discussion), Fuzzy contrllers (overview and example).
Fuzzy system & neural network, Fuzzy automata, Pattern recognition (introduction), Fuzzy clusteing, Fuzzy pattern recognition, Fuzzy image processing.
1. Fuzzy set theory & application – by G.J.Klir and Folger
2. Fuzzy sets and Fuzzy logic theory and application – by George J. Klir and Bo Yuan, PHI publication, 1997
3. Neural Networks and Fuzzy Systems : A Dynamic Systems Approch to Machine Intelligence – by B.Kosko, PHI publication, 1997
4. Neutral Networks in Computer Intelligence – by Limin Fu, McGraw Hill International, 1994
5. Introduction to the Theory of Neural Computations – by John Hertz, Addision Wesely, 1991
(4). Neural Networks and Application
Introduction to Neural Networks : Biological and Artificial Neuraons, Perceptrons classification and Linear Separability X-OR problem, Hopfield Networks, Overview of Neural Networks Architectures-Multiayered feed forward and Recuerrent Networks. Learning-Supervised, Unsupervised and Reinforcement, Generalised Delta Rule.
Multilayered Networks : Backpropagation (BP) Networks, BP Training Algorithm and Derivation for Adaption of weight, variations in Back propagation and Alternative cost function, Rudial Basis function (RBF) Networks, Applications of BP and RBF Networks.
Recurrent Networks and Unsupervised Learning : Counter Back propagation Networks, Boltzman Machine, Unsupervised learning methods, Hebbian learning Kohonen’s Self Organizing feature maps, Adaptive Resonance Theory.
Associative Memories : Matrix, Auto, Hetero and Bidirectional Associative memories, Applications of Assciative Memories. Neuro Fuzzy System : Relevance of Integration between Fuzzy Sets and Neural Networks-pros and cons, Fuzzy Neurons, Fuzzy Neuro Controllers.
Neuro Computation : Domains of Application of Neural Networks – Expert System & Decision Making system, Pattern Recognition, Neuro Controllers and Fuzzy Neuro Controllers.
1. B.Koko “Neural Networks and Fuzzy System : A Dynamical System Approach to Machine Intelligence”, Printice Hall of India (PHI), 1997
2. Limin Fu, “Neural Networks in Computer Intelligence”, McGraw Hill International, 1994
3. John Hertz, Anders Krogh and Richard G. Palmer, “Introduction to the Theory of Neural Computations”, Addison Wesely 1991
4. Yoh-Han Pao, Adaptive Pattern Recognition and Neural Networks”, Addision Wesely 1989.
(5) Internet Technologies and Applications
Network Layer Function and Protocols : Switching, Routing and congestion control, X.25, Internet Protocol (IP).
Transport Layer Function and Protocols : Addressing flow control, Connection management, multiplexing, Transmission Control Protocol (TCP) and User Datagram Protocol (UDP), Socket and TLI interface.
Application Layer Services and Protocols : Domain Name Services, network
Management protocol , electronic mail and file transfer protocol , World Wide Web.
Unit IV :
Survey of Contemporary Internet Technologies : Role, use and implimentation of
Current tools ; Basic TCP/IP, name space, correctness and protocols; World Wide
Web/HTML Techniques for text, images, links and forms; Indexin gmethods : gopher,
WAIS; Server site programming, CGI scripts; Security issues.
Emphasis on understanding, exploring and extending internet technologies using Java or Pearl.
1. Computer Networks – by Andrew Tenebaum,PHI , Third edition.
2. Computer and Data Communication – by William Stalling, PHI, Fifth edition.
3. Programming with Jave : A Primer – by E.Balaguruswamy, McGraw International.
4. Java 2 : The Complete Reference – by Naughton Patrick & Herbert Schildt, McGraw Hill International.
The Project gives an opportunity to the student to use the methodologies/techniques taugh in several courses in the curriculam. The topics for the project to be undertaken by the departmen, after deliberations among the faculty members, shall be notified to the students. The project is to be carried out under the guidance of a faculty member of the department. A student should submit 3 copies of dissertation for evaluation at the end of the semester and present his project as a seminar topic. The external examiner in consultation with the internal examiner shall carry out the adjudication, after giving due weightage to the work carried out in the project, the presentation of the project, and viva voca. The guide/supervisor will be the internal exminer and external shall be appointed from a panel of eaminers.
Marks Distribution :
Internal Assessment – 75 marks
Dissertation – 150 marks
Viva Voce - 75 marks