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

Lingaya’s University, Faridabad4 bit code algorithm, Sutherland-Cohen algorithm,parametric line clipping algorithm (Cyrus Beck).3. POLYGON CLIPPING ALGORITHM: Sutherland-Hodgeman polygon clipping algorithm,homogeneous coordinates system, twodimensional transformations: transformations,translation, scaling, rotation, reflection, shearing,transformation, composite transformation.4. THREE DIMENSIONAL GRAPHICS: Threedimensional graphics concept, matrixrepresentation of 3-D transformations, compositionof 3-D transformation; viewing in 3D: projections,types of projections; the mathematics of plannergeometric projections; coordinate systems.5. HIDDEN SURFACE REMOVAL: Introduction tohidden surface removal; the Z- buffer algorithm,scan-line algorithm, area sub-division algorithm.6. REPRESENTING CURVES AND SURFACES:Parametric representation of curves: Beziercurves, B-Spline curves; parametric representationof surfaces; interpolation method.7. ILLUMINATION, SHADING, IMAGEMANIPULATION: Illumination models, shadingmodels for polygons, shadows, transparency; whatis an image, filtering, image processing, geometrictransformation of images.TEXT BOOKFoley James D., van Dam Andeies, Feiner Stevan K.and Hughes Johb F., “Computer Graphics Principlesand Practices”, 2nd Edition, Addision Wesley, 2000REFERENCE BOOKS1. Hearn Donald and Baker M. Pauline, “ComputerGraphics”, 2nd Edition, Prentice Hall of India, 19992. Rogers David F., “Procedural Elements forComputer Graphics”, 2nd Edition, Tata McGrawHill, 20013. Watt Alan, “Fundamentals of 3-DimensionalComputer Graphics”, Addision Wesley, 19994. John Corrign, “Computer Graphics: Secrets andSolutions”, BPB Publications, 19945. Krishanmurthy N., “Introduction to ComputerGraphics”, Tata McGraw Hill, 2002WEB REFERENCES1. http://en.wikipedia.org/wiki/Computer_graphics2. http://www.cgw.com/ME2/Default.asp3. http://www.graphics.cornell.edu/online/tutorial/4. http://graphics.stanford.edu/CS-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, Knight Kevin and Nair, “ArtificialIntelligence”, 3rd Edition, Tata McGraw Hill, 2009REFERENCE BOOKS1. Nilson Nils J., “Artificial Intelligence”, New YorkMcGraw-Hill, 1971.2. 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”,Narosa Publications, 3rd Edition, 2002.WEB REFERENCES1. http://wwwformal.stanford.edu/jmc/whatisai/2. http://library.thinkquest.org/2705/3. www.imdb.com.71