Intelligent Control Based on Flexible Neural Networks / Edition 1

Intelligent Control Based on Flexible Neural Networks / Edition 1

by M. Teshnehlab, Watanabe Kyoko
     
 

The use of flexible sigmoid functions makes artificial neural networks more versatile. This volume determines learning algorithms for sigmoid functions in several different learning modes using flexible structures of neural networks with new derivation algorithms.
The book is aimed at electrical, electronic, and mechanical control and systems engineers

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Overview

The use of flexible sigmoid functions makes artificial neural networks more versatile. This volume determines learning algorithms for sigmoid functions in several different learning modes using flexible structures of neural networks with new derivation algorithms.
The book is aimed at electrical, electronic, and mechanical control and systems engineers concerned with intelligent control who wish to explore neural network approaches. Here, for readers who are unfamiliar with neural network computing, is a concise introduction to the main existing types of flexible neural networks. This book will be a valuable aid to new research in which high abilities in artificial neural networks in intelligent control design and development can be achieved.

Product Details

ISBN-13:
9780792356837
Publisher:
Springer Netherlands
Publication date:
06/30/1999
Series:
Intelligent Systems, Control and Automation: Science and Engineering Series, #19
Edition description:
1999
Pages:
236
Product dimensions:
0.69(w) x 6.14(h) x 9.21(d)

Meet the Author

Table of Contents

Acknowledgements. Preface. 1. Introduction. 2. Fundamentals of Neural Networks. 3. Flexible Neural Networks. 4. Self-Tuning PID Control. 5. Self-Tuning Computed Torque Control: Part I. 6. Self-Tuning Computed Torque Control: Part II. 7. Development of an Inverse Dynamics Model. 8. Self-organizing Flexible Neural Network. 9. Conclusions.

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