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Studies in Fuzziness and Soft Computing

Knowledge-Based Neurocomputing: A Fuzzy Logic Approach

Authors: Kolman, Eyal, Margaliot, Michael

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  • Presents the state-of-the-art in knowledge-based neurocomputing
  • Presents a new connection between artificial neural networks (ANNs) and a special fuzzy-rule base—the all permutations fuzzy-rule base (FARB)
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eBook $139.00
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  • ISBN 978-3-540-88077-6
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Hardcover $179.99
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Softcover $209.00
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About this book

In this monograph, the authors introduce a novel fuzzy rule-base, referred to as the Fuzzy All-permutations Rule-Base (FARB). They show that inferring the FARB, using standard tools from fuzzy logic theory, yields an input-output map that is mathematically equivalent to that of an artificial neural network. Conversely, every standard artificial neural network has an equivalent FARB.

The FARB-ANN equivalence integrates the merits of symbolic fuzzy rule-bases and sub-symbolic artificial neural networks, and yields a new approach for knowledge-based neurocomputing in artificial neural networks.

Table of contents (7 chapters)

Table of contents (7 chapters)

Buy this book

eBook $139.00
price for USA in USD
  • ISBN 978-3-540-88077-6
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $179.99
price for USA in USD
Softcover $209.00
price for USA in USD
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Bibliographic Information

Bibliographic Information
Book Title
Knowledge-Based Neurocomputing: A Fuzzy Logic Approach
Authors
Series Title
Studies in Fuzziness and Soft Computing
Series Volume
234
Copyright
2009
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-540-88077-6
DOI
10.1007/978-3-540-88077-6
Hardcover ISBN
978-3-540-88076-9
Softcover ISBN
978-3-642-09985-4
Series ISSN
1434-9922
Edition Number
1
Number of Pages
XVI, 100
Topics