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Neural networks and fuzzy systems : theory and applications

Neural networks and fuzzy systems : theory and applications (Loan 2 times)

Material type
단행본
Personal Author
Abe, Shigeo. Ralescu, Anca.
Title Statement
Neural networks and fuzzy systems : theory and applications / Shigeo Abe ; foreword by Anca Ralescu.
Publication, Distribution, etc
Boston :   Kluwer Academic,   c1997.  
Physical Medium
xvi, 258 p. : ill. ; 25 cm.
ISBN
0792398149 (acid-free paper)
Bibliography, Etc. Note
Includes bibliographical references (p. [225]-242) and index.
Subject Added Entry-Topical Term
Neural networks (Computer science). Fuzzy systems.
000 00794camuuu200241 a 4500
001 000000975773
005 19990122105455.0
008 960906s1997 maua b 001 0 eng
010 ▼a 96043309
020 ▼a 0792398149 (acid-free paper)
040 ▼a DLC ▼c DLC ▼d DLC ▼d 244002
049 0 ▼l 151055533
050 0 0 ▼a QA76.87 ▼b .A32 1997
082 0 0 ▼a 006.3 ▼2 20
090 ▼a 006.3 ▼b A138n
100 1 ▼a Abe, Shigeo.
245 1 0 ▼a Neural networks and fuzzy systems : ▼b theory and applications / ▼c Shigeo Abe ; foreword by Anca Ralescu.
260 ▼a Boston : ▼b Kluwer Academic, ▼c c1997.
300 ▼a xvi, 258 p. : ▼b ill. ; ▼c 25 cm.
504 ▼a Includes bibliographical references (p. [225]-242) and index.
650 0 ▼a Neural networks (Computer science).
650 0 ▼a Fuzzy systems.
700 1 ▼a Ralescu, Anca.

Holdings Information

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Contents information

Book Introduction

Neural Networks and Fuzzy Systems: Theory and Applications discusses theories that have proven useful in applying neural networks and fuzzy systems to real world problems. The book includes performance comparison of neural networks and fuzzy systems using data gathered from real systems. Topics covered include the Hopfield network for combinatorial optimization problems, multilayered neural networks for pattern classification and function approximation, fuzzy systems that have the same functions as multilayered networks, and composite systems that have been successfully applied to real world problems. The author also includes representative neural network models such as the Kohonen network and radial basis function network. New fuzzy systems with learning capabilities are also covered.
The advantages and disadvantages of neural networks and fuzzy systems are examined. The performance of these two systems in license plate recognition, a water purification plant, blood cell classification, and other real world problems is compared.

Neural Networks and Fuzzy Systems: Theory and Applications discusses theories that have proven useful in applying neural networks and fuzzy systems to real world problems. The book includes performance comparison of neural networks and fuzzy systems using data gathered from real systems. Topics covered include the Hopfield network for combinatorial optimization problems, multilayered neural networks for pattern classification and function approximation, fuzzy systems that have the same functions as multilayered networks, and composite systems that have been successfully applied to real world problems. The author also includes representative neural network models such as the Kohonen network and radial basis function network. New fuzzy systems with learning capabilities are also covered.
The advantages and disadvantages of neural networks and fuzzy systems are examined. The performance of these two systems in license plate recognition, a water purification plant, blood cell classification, and other real world problems is compared.


Information Provided By: : Aladin

Table of Contents

Foreword; Anca Ralescu. Preface. Introduction. 1. Overview of Neural Networks. 2. The Hopfield Network. 3. Multilayered Networks. 4. Other Neural Networks. 5. Overview of Fuzzy Systems. 6. Fuzzy Rule Extraction for Pattern Classification from Numerical Data. 7. Fuzzy Rule Extraction for Function Approximation from Numerical Data. 8. Composite Systems. References. Solutions to Problems. Index: Subject Index. Author Index.


Information Provided By: : Aladin

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