Fuzzy Logic And Neural Networks

Contents: 1. Introduction. 2. Fuzzy Sets and Classical Sets. 3. Fuzzy Relations and Classical Relations. 4. Membership Functions. 5. Classical Logic and Fuzzy Logic. 6.Fuzzy Rule Based Systems. 7. Fuzzy to Crisp Conversions. 8. Fuzzy Classification and Pattern Recognition. 9. Fuzzy Control Systems. 10. Fundamental Concepts. 11. Models of Artificial Neural Systems. 12. Common Neural Nets. Appendix. Glossary. Bibliography. Question Bank.

This book is designed to meet the requirements of Engineering students in Electronics and instrumentation, electrical and electronics, computer science and information technology. This book explains the fundamentals of fuzzy logic and neural networks with suitable examples for better understanding. Other features include: Basic Fuzzy set theory is made simple. Different techniques involved in Fuzzy Logic Control System Design have been highlighted. Application like pattern Recognition and classification dealt in detail. Different algorithms and models of artificial neural systems are given with suitable example.