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Fuzzy and Neural: Interactions and Applications

  • Book
  • © 1998

Overview

Authors:
  1. James J. Buckley

    1. Mathematics Department, University of Alabama at Birmingham, Birmingham, USA

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    You can also search for this author in PubMed   Google Scholar

  2. Thomas Feuring

    1. Department of Electrical and Computer Science, University of Siegen, Siegen, Germany

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    You can also search for this author in PubMed   Google Scholar

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 25)

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Table of contents (12 chapters)

  1. Front Matter

    Pages I-XIII
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  2. Introduction

    • James J. Buckley, Thomas Feuring
    Pages 1-2

  3. Fuzzy Sets and Fuzzy Functions

    • James J. Buckley, Thomas Feuring
    Pages 3-19

  4. Neural Nets

    • James J. Buckley, Thomas Feuring
    Pages 21-34

  5. First Approximation Results

    • James J. Buckley, Thomas Feuring
    Pages 35-48

  6. Hybrid Neural Nets

    • James J. Buckley, Thomas Feuring
    Pages 49-63

  7. Neural Nets Solve Fuzzy Problems

    • James J. Buckley, Thomas Feuring
    Pages 65-75

  8. Fuzzy Neural Nets

    • James J. Buckley, Thomas Feuring
    Pages 77-96

  9. Second Approximation Results

    • James J. Buckley, Thomas Feuring
    Pages 97-110

  10. Hybrid Fuzzy Neural Nets

    • James J. Buckley, Thomas Feuring
    Pages 111-117

  11. Applications of Hybrid Fuzzy Neural Nets and Fuzzy Neural Nets

    • James J. Buckley, Thomas Feuring
    Pages 119-132

  12. Fuzzy Teaching Machine

    • James J. Buckley, Thomas Feuring
    Pages 133-147

  13. Summary, Future Research and Conclusions

    • James J. Buckley, Thomas Feuring
    Pages 149-157

  14. Back Matter

    Pages 159-161
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Keywords

About this book

The primary purpose of this book is to present information about selected topics on the interactions and applications of fuzzy + neural. Most of the discussion centers around our own research in these areas. Fuzzy + neural can mean many things: (1) approximations between fuzzy systems and neu­ ral nets (Chapter 4); (2) building hybrid neural nets to equal fuzzy systems (Chapter 5); (3) using neura.l nets to solve fuzzy problems (Chapter 6); (4) approximations between fuzzy neural nets and other fuzzy systems (Chap­ ter 8); (5) constructing hybrid fuzzy neural nets for certain fuzzy systems (Chapters 9, 10); or (6) computing with words (Chapter 11). This book is not intend to be used primarily as a text book for a course in fuzzy + neural because we have not included problems at the end of each chapter, we have omitted most proofs (given in the references), and we have given very few references. We wanted to keep the mathematical prerequisites to a minimum so all longer, involved, proofs were omitted. Elementary dif­ ferential calculus is the only prerequisite needed since we do mention partial derivatives once or twice.

Authors and Affiliations

  • Mathematics Department, University of Alabama at Birmingham, Birmingham, USA

    James J. Buckley

  • Department of Electrical and Computer Science, University of Siegen, Siegen, Germany

    Thomas Feuring

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