This well-organized and clearly-presented book offers a detailed understanding of the constituent methodologies underlying neuro-fuzzy and soft computing-an evolving branch of computational intelligence which is aimed at solving real-world decision making, modeling, and control problems. It is intended for use as a text for computer science and computer engineering students. The methodologies covered include "fuzzy set theory, neural networks, data clustering techniques, and several gradient-free stochastic optimization methods-with equal emphasis on their theoretical aspects as well as empirical observations and verifications of various applications in practice. Many step-by-step examples are included to complement explanations in the text. The book contains many specially designed figures generated by MATLAB and SIMULINK to help visualize the process of fuzzy reasoning, neural-network learning, neuro-fuzzy integration and training, and many other ideas and concepts. End-of-chapter exercises are designed to reinforce understanding of the material presented, as well as to equip the reader with hands-on programming experiences for practical problem solving. Hints to selected exercises are provided in the appendix. All MATLAB programs used in the book can be obtained via FTP or WWW. The book also contains an 'Internet Resource Page' to point the reader to on-line neuro-fuzzy and soft computing home pages, publications, public-domain software, research institutes, news groups, etc.

Table of Contents
Foreword. Preface. 1. Introduction to Neuro-Fuzzy and Soft Computing. I: FUZZY SET THEORY-2. Fuzzy Sets. 3. Fuzzy Rules and Fuzzy Reasoning. 4. Fuzzy Inference Systems. II: REGRESSION AND OPTIMIZATION-5. Least-Squares Methods for System Identification. 6. Derivative-based Optimization. 7. Derivative-Free Optimization. III: NEURAL NETWORKS-8. Adaptive Networks. 9. Supervised Learning Neural Networks. 10. Learning from Reinforcement. 11. Unsupervised Learning and Other Neural Networks. IV: NEURO-FUZZY MODELING-12. ANFIS: Adaptive Neuro-Fuzzy Inference Systems. 13. Coactive Neuro-Fuzzy Modeling: Towards Generalized ANFIS. V: ADVANCED NEURO-FUZZY MODELING-14. Classification and Regression Trees. 15. Data Clustering Algorithms. 16. Rulebase Structure Identification. VI: NEURO-FUZZY CONTROL-17. Neuro-Fuzzy Control I. 18. Neuro-Fuzzy Control II. VII: ADVANCED APPLICATIONS-19. ANFIS Applications. 20. Fuzzy-Filtered Neural Networks. 21. Fuzzy Sets and Genetic Algorithms in Game Playing. 22. Soft Computing for Color Recipe Prediction. A. Hints to Selected Exercises. B. List of Internet Resources. C. List of MATLAB Programs. D. List of Acronyms. Index.