Neural networks and fuzzy systems : theory and applications

著者

書誌事項

Neural networks and fuzzy systems : theory and applications

Shigeo Abe ; foreword by Anca Ralescu

Kluwer Academic, c1997

タイトル別名

ニューラルネットとファジィシステム : 理論と応用

大学図書館所蔵 件 / 全15件

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注記

Includes bibliographical references and indexes

内容説明・目次

内容説明

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.

目次

  • 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.

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