Fuzzy logic and neural networks: basic concepts & application

About the Book: The primary purpose of this book is to provide the student with a comprehensive knowledge of basic concepts of fuzzy logic and neural networks. The hybridization of fuzzy logic and neural networks is also included. No previous knowledge of fuzzy logic and neural networks is required. Fuzzy logic and neural networks have been discussed in detail through illustrative examples, methods and generic applications. Extensive and carefully selected references is an invaluable resource for further study of fuzzy logic and neural networks. Each chapter is followed by a question bank which is intended to help in the preparation for external examination. This book consists of 125 illustrations. Contents: Introduction Part I: Fuzzy Logic Fuzzy Sets and Fuzzy Logic Fuzzy Relations Fuzzy Implications The Theory of Approximate Reasoning Fuzzy Rule-Based Systems Fuzzy Reasoning Schemes Fuzzy Logic Controllers Fuzzy Logic Applications Part II: Neural Networks Fundamentals Perceptron and Adaline Back-Propagation Recurrent Networks Self-Organising Networks Reinforcement Learning Neural Networks Applications Part III: Hybrid Fuzzy Neural Networks Hybrid Fuzzy Neural Networks Hybrid Fuzzy Neural Networks Applications.