Flexible Neuro-Fuzzy Systems

Structures, Learning and Performance Evaluation

  • Leszek¬†Rutkowski

Part of the The International Series in Engineering and Computer Science book series (SECS, volume 771)

About this book

Introduction

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.

Keywords

algorithms classification fuzzy fuzzy system fuzzy systems learning modeling robot robotics simulation system modeling

Authors and affiliations

  • Leszek¬†Rutkowski
    • 1
  1. 1.Technical University of CzestochowaPoland

Bibliographic information

  • DOI https://doi.org/10.1007/b115533
  • Copyright Information Kluwer Academic Publishers 2004
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4020-8042-5
  • Online ISBN 978-1-4020-8043-2
  • Series Print ISSN 0893-3405
  • About this book