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B.Tech. Degree Programme Electrical Engineering - Lingaya's ...

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Lingaya’s University, Faridabad3. Barkakati, Nabajyoti, “Object Oriented Programmingin C++”, Prentice Hall of India, 2001.4. Schildt, Herbert, “C++: The Complete Reference”,Tata McGraw Hill, 4 th Edition, 2003CS-402ARTIFICIAL INTELLIGENCEL T P Cr5 0 0 3OBJECTIVETo introduce about artificial intelligence approaches toproblem solving, various issues involved andapplication areasPRE-REQUISITESKnowledge of neural networks, data structures1. INTRODUCTION TO AI AND SEARCHTECHNIQUES: Foundation and history of AI; data,information and knowledge; AI problems andtechniques – AI programming languages, problemspace representation with examples; blind searchstrategies, breadth first search, depth first search,heuristic search techniques: hill climbing: best firstsearch, A * algorithm AO* algorithm, Means-endsanalysis.2. KNOWLEDGE REPRESENTATION ISSUES:predicate logic; logic programming; constraintpropagation; representing knowledge usingrules.3. REASONING UNDER UNCERTAINITY:Reasoning under uncertainty, non monotonicreasoning; review of probability; Bayes’probabilistic interferences and Dempster Shafertheory; heuristic methods; symbolic reasoningunder uncertainty; statistical reasoning, fuzzyreasoning.4. PLANNING & GAME PLAYING: Minimax searchprocedure; goal stack planning; non linearplanning, hierarchical planning, planning insituational calculus; representation for planning;partial order planning algorithm5. LEARNING: Basic concepts; rote learning,learning by taking advices, learning by problemsolving, learning from examples, discovery aslearning, learning by analogy; explanation basedlearning; neural nets; genetic algorithms.6. OTHER KNOWLEDGE STRUCTURES: semanticnets, partitioned nets, parallel implementation ofsemantic nets; frames, common sense reasoningand thematic role frames; architecture ofknowledge based system; rule based systems;forward and backward chaining; frame basedsystems.7. APPLICATIONS OF ARTIFICIALINTELLIGENCE: Principles of natural languageprocessing; rule based systems architecture;expert systems, knowledge acquisition concepts;AI application to robotics, and current trends inintelligent systems; parallel and distributed AI:psychological modeling, parallelism in reasoningsystems, distributed reasoning systems andalgorithmsTEXT BOOKRich Elaine and Knight Kevin, “Artificial Intelligence”,3rd Edition, Tata McGraw Hill, 1991REFERENCE BOOKS1. Nilson Nils J., “Artificial Intelligence”, McGraw-Hill,New York 19712. Russell Stuart and Norvig Peter, “ArtificialIntelligence: A Modern Approach”, Prentice Hall ofIndia, 19983. Negnevitsky, “Artificial Intelligence: A Guide toIntelligent System”, Pearson Education, 2004.4. Patterson O. W., “Introduction to ArtificialIntelligence & Expert Systems”, Prentice Hall ofIndia, 1996.5. Winston Patrick Henry, “Artificial Intelligence”, 3rdEdition, Addition Wesley, 19926. Clockson & Mellish, “Programming PROLOG”, 3rdEdition, Narosa Publications, 2002.WEB REFERENCES1. http://wwwformal.stanford.edu/jmc/whatisai/2. http://library.thinkquest.org/2705/3. www.imdb.com.EC-201ELECTRONICS L T P CrENGINEERING 5 1 0 4OBJECTIVEThe purpose of this course is to give basic electronicsconcept; their operational significance and its basicapplication.PRE-REQUISITESKnowledge of electricity, solid state physics1. HISTORICAL BACKGROUND: Vacuum tubes;working of vacuum tube and their characteristics;vacuum diode; triode; tetrode and pentode2. PN JUNCTION: Depletion layer; Barrier potential;Forward and reverse bias; Breakdown voltage;PIV; switching characteristics of p-n junction diode;knee voltage; load line; and operating Point Idealp-n junction diode; junction capacitance; zenerdiode.3. RECTIFIERS AND FILTERS: Half wave; centretap full wave and bridge rectifier; percentage ofregulation; PIV; ripple factor; C; RC; LC and PIfilter; voltage doubler; clipping and clampingcircuit; voltage regulation.4. BIPOLAR JUNCTION TRANSISTOR:Introduction; basic theory of operation of PNP adNPN transistor-l characteristics; CB; CE and CCconfiguration; different biasing techniques.5. FET: Introduction; Theory of operation; JFETParameters; and JFET Amplifiers. MOSFET:Introduction; theory of operation; MOSFETparameters; application; graphical analysis of BJTand FET circuits; linear models of BJT and FET;pulse and large signal models of BJT and FET6. BIASING TECHNIQUES OF FET: Introductoryidea of multistage and feedback amplifiers; basebias; emitter feedback bias; collector voltagedivider bias; Load line and operating point.7. INTEGRATED CIRCUIT: Analysis of principle ofintegration. Introduction to Digital Integratedcircuits; THYRISTORS: Introduction to thyristorfamily; SCR theory of operation; SCRcharacteristics and triggering; TRIAC: Theory of27

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