Flexible Neuro-Fuzzy Systems, 2004 Structures, Learning and Performance Evaluation The Springer International Series in Engineering and Computer Science Series, Vol. 771

Flexible Neuro-Fuzzy Systems is the first professional literature about the new class of powerful, flexible fuzzy systems. The author incorporates various flexibility parameters to the construction of neuro-fuzzy systems. This approach dramatically improves their performance, allowing the systems to perfectly represent the pattern encoded in data.
Flexible Neuro-Fuzzy Systems is the only book that proposes a flexible approach to fuzzy modeling and fills the gap in existing literature. This book introduces new fuzzy systems which outperform previous approaches to system modeling and classification, and has the following features:

-Provides a framework for unification, construction and development of neuro-fuzzy systems;
-Presents complete algorithms in a systematic and structured fashion, facilitating understanding and implementation,
-Covers not only advanced topics but also fundamentals of fuzzy sets,
-Includes problems and exercises following each chapter,
-Illustrates the results on a wide variety of simulations,
-Provides tools for possible applications in business and economics, medicine and bioengineering, automatic control, robotics and civil engineering.

Foreword. 1. Introduction. 2. Elements Of The Theory Of Fuzzy Sets. 3. Fuzzy Inference Systems. 4. Flexibility In Fuzzy Systems. 5. Flexible Or-Type Neuro-Fuzzy Systems. 6. Flexible Compromise And-Type Neuro-Fuzzy Systems. 7. Flexible Mamdani-Type Neuro-Fuzzy Systems. 8. Flexible Logical-Type Neuro-Fuzzy Systems. 9. Performance Comparison Of Neuro-Fuzzy Systems. Appendix. Bibliography. Index.