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Fuzzy neural network theory and application /

This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. S...

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Bibliographic Details
Main Authors: Liu, Puyin
Corporate Authors: World Scientific Firm
Group Author: Li, Hong-Xing, 1953
Published: World Scientific Pub. Co.,
Publisher Address: Singapore ; River Edge, N.J. :
Publication Dates: 2004.
Literature type: eBook
Language: English
Series: Series in machine perception and artificial intelligence ; v. 59
Subjects:
Neural networks Computer science
Fuzzy systems
Electronic books
Online Access: http://www.worldscientific.com/worldscibooks/10.1142/5493#t=toc
Summary: This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to
Carrier Form: 1 online resource (xvii,376pages) : illustrations.
Bibliography: Includes bibliographical references.
ISBN: 9789812794215 (electronic bk.)
CLC: TP183
Contents: ch. I. Introduction. 1.1. Classification of fuzzy neural networks. 1.2. Fuzzy neural networks with fuzzy operators. 1.3. Fuzzified neural networks. 1.4. Fuzzy systems and fuzzy inference networks. 1.5. Fuzzy techniques in image restoration. 1.6. Notations and preliminaries. 1.7. Outline of the topics of the chapters -- ch. II. Fuzzy neural networks for storing and classifying. 2.1. Two layer max-min fuzzy associative memory. 2.2. Fuzzy [symbol]-learning algorithm. 2.3. BP learning algorithm of FAM's. 2.4. Fuzzy ART and fuzzy ARTMAP -- ch. III. Fuzzy associative memory - feedback networks. 3.

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