MD3001 PATTERN RECOGNITION AND AI TECHNIQUES SYLLABUS | ANNA UNIVERSITY BE MEDICAL ELECTRONICS ENGINEERING 6TH SEMESTER SYLLABUS REGULATION 2008 2011 2012-2013 BELOW IS THE ANNA UNIVERSITY SIXTH SEMESTER B.E MEDICAL ELECTRONICS ENGINEERING DEPARTMENT SYLLABUS, TEXTBOOKS, REFERENCE BOOKS,EXAM PORTIONS,QUESTION BANK,PREVIOUS YEAR QUESTION PAPERS,MODEL QUESTION PAPERS, CLASS NOTES, IMPORTANT 2 MARKS, 8 MARKS, 16 MARKS TOPICS. IT IS APPLICABLE FOR ALL STUDENTS ADMITTED IN THE YEAR 2011 2012-2013 (ANNA UNIVERSITY CHENNAI,TRICHY,MADURAI, TIRUNELVELI,COIMBATORE), 2008 REGULATION OF ANNA UNIVERSITY CHENNAI AND STUDENTS ADMITTED IN ANNA UNIVERSITY CHENNAI DURING 2009
MD3001 PATTERN RECOGNITION AND AI TECHNIQUES LT P C
3 0 0 3
UNIT I INTRODUCTION 9
Definition of AI, Intelligent agents, perception and language processing, problem solving,
searching, heuristic searching, game playing, logics, logical reasoning.
UNIT II BASIC PROBLEMS SOLVING METHODS 9
Forward Vs background, knowledge representation, frame problems, heuristic functions,
weak methods of matching.
UNIT III PRINCIPLES OF PATTERN RECOGNITION 9
Patterns and features, training and learning in pattern recognition approach, different
types of pattern recognition.
UNIT IV DECISION MAKING 9
Baye’s theorem, multiple features, decision boundaries, estimation of error rates,
histogram, kernels, window estimaters, nearest neighbour classification, maximum
distance pattern clssifiers, adaptive decision boundaries.
UNIT V CLUSTER ANALYSIS AND FEATURE EXTRACTION 9
Unsupervised learning, heirarchial clustering, graph theories approach to pattern
clustering, fuzzy pattern classifiers, application of pattern recognition in medicine.
TOTAL: 45 PERIODS
REFERENCES:
1. Elain Rich and Kevin Knight, “Artificial Intelligence” Tata McGraw-Hill, 2 nd Edition,
Edition- 1993.
2. Dan W. Patterson, “Introduction to Artificial Intelligence and Expert Systems”,
Prentice Hall of India, Delhi, Edition- 2001.
3. Earl Gose, Richard Johnsonbaugh, Steve Jost, “Pattern Recognition and Image
Analysis”, Prentice Hall of India Pvt. Ltd., New Delhi, Edition- 1999.
4. G.F. Luger & W.A Stubble Field, “Artificial intelligence structures and Strategies f
or complex problem solving,” 3 rd Edition, Pearson Education, Edition- 1998.
5. Efrain Turban and Jay E Aranson: “Decision support systems and Intelligent
Systems,” 5th Edition, Pearson Education, 1998.
MD3001 PATTERN RECOGNITION AND AI TECHNIQUES LT P C
3 0 0 3
UNIT I INTRODUCTION 9
Definition of AI, Intelligent agents, perception and language processing, problem solving,
searching, heuristic searching, game playing, logics, logical reasoning.
UNIT II BASIC PROBLEMS SOLVING METHODS 9
Forward Vs background, knowledge representation, frame problems, heuristic functions,
weak methods of matching.
UNIT III PRINCIPLES OF PATTERN RECOGNITION 9
Patterns and features, training and learning in pattern recognition approach, different
types of pattern recognition.
UNIT IV DECISION MAKING 9
Baye’s theorem, multiple features, decision boundaries, estimation of error rates,
histogram, kernels, window estimaters, nearest neighbour classification, maximum
distance pattern clssifiers, adaptive decision boundaries.
UNIT V CLUSTER ANALYSIS AND FEATURE EXTRACTION 9
Unsupervised learning, heirarchial clustering, graph theories approach to pattern
clustering, fuzzy pattern classifiers, application of pattern recognition in medicine.
TOTAL: 45 PERIODS
REFERENCES:
1. Elain Rich and Kevin Knight, “Artificial Intelligence” Tata McGraw-Hill, 2 nd Edition,
Edition- 1993.
2. Dan W. Patterson, “Introduction to Artificial Intelligence and Expert Systems”,
Prentice Hall of India, Delhi, Edition- 2001.
3. Earl Gose, Richard Johnsonbaugh, Steve Jost, “Pattern Recognition and Image
Analysis”, Prentice Hall of India Pvt. Ltd., New Delhi, Edition- 1999.
4. G.F. Luger & W.A Stubble Field, “Artificial intelligence structures and Strategies f
or complex problem solving,” 3 rd Edition, Pearson Education, Edition- 1998.
5. Efrain Turban and Jay E Aranson: “Decision support systems and Intelligent
Systems,” 5th Edition, Pearson Education, 1998.
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