504198 ELECTIVE II
MACHINE INTELLIGENCE
Teaching Scheme Examination Scheme
Lectures: 3 Hrs./Week Theory: 100 Marks
Credit: 3
Introduction, Soft Computing intelligence, comparison with conventional Artificial
Intelligence, soft computing characteristics, Fuzzy sets, Fuzzy rules and Fuzzy inference
systems, Different fuzzy Models : Mamdani, Sugeno, Tsu Kamoto, Fuzzy modeling, Least
squares methods for system identification, Derivative based optimization.
Neural networks, Adaptive networks, Supervised learning Neural networks,
Perceptron, Backpropagation Multilayer perception, Radial basis function networks, Learning
from reinforcement, Dynamic programming, Competitive learning, Kohonen’s self organizing
networks, Principle component networks, LVQ, Hopfield networks.
Adaptive Neuro-Fuzzy interface systems, Advanced Neuro-Fuzzy modeling,
Data clustering algorithms, Neuro-Fuzzy control, Fuzzy filtered neural network,
Genetic algorithms in game playing.
References
1. S. R. Jang, C.T. Sun, E. Mizutani,‘ Neuro-Fuzzy and Soft Computing’, Pearson
Education, ISBN 81-297-0324-6.
2. B. Kosko, ‘Neural Networks and Fuzzy Systems: a dynamical systems approach’
Prentice Hall Publication.
3. Simon Haykin, ‘ Neural Networks: Comprehensive Foundation’, Prentice Hall, ISBN-
10: 0132733501.
4. Jacek M. Zurada , ‘Introduction to Artificial Neural Systems’, Jaico publications
Reference http://www.unipune.ernet.in/stud_info/Syllabi/Syllabus_2008.html
|
No responses found. Be the first to respond...
|