Course

Unit 1

Basic Concepts – Single Layer Perception – Multilayer Perception – Supervised and Unsupervised Learning – Back Propagation networks – Kohnen’s self-organizing networks – Hop field networks – Distance measures.

Unit 2

FUZZY sets, properties, Membership functions Fuzzy operations, Applications.

Unit 3

Classification and Regression Trees – Data Clustering Algorithms – Rule based Structure identification.

Unit 4

Neuro-Fuzzy Systems.

Unit 5

Evolutionary Computation – Survival of the Fittest – Fitness Computation – Crossover – Mutation – Reproduction – Rank space Method. Case Studies: Applications of soft computing.

1. Laurence Fausett,”Fundamentals of Neural Networks”, Seventh Edition, Dorling Kindersley (India) P. Ltd 2006.
2. Satish Kumar – “Neural Networks – A Classroom Approach”, Tata McGraw-Hill, 2004.
3. Timothy J.Rose, ”Fuzzy Logic with Engineering Applications”, Third Edition, John Wiley, 2010.
4. J.S.R Jang,C.T Sun and E.Mizutani, ”Neuro-Fuzzy and Soft Computing”, Second Edition, Prentice Hall of India, 2002.
5. D.E.Goldberg ”Genetic Algorithms in search, optimization and Machine learning”, Second Edition, Addison Wesley, 2007.