Neural Networks and Fuzzy Systems : Theory and Applications

Shigeo Abe

ISBN 10: 0792398149 / ISBN 13: 9780792398141

Published by Springer US, Springer US, 1996

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9780792398141

Bibliographic Details

• Title: Neural Networks and Fuzzy Systems : Theory and Applications
• Publisher: Springer US, Springer US
• Publication Date: 1996
• Language: English
• ISBN 10: 0792398149
• ISBN 13: 9780792398141
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 20D millimeters 241 millimeters width by 160 millimeters height by 20 millimeters depth
• Weight: 594 grams

About this title

Synopsis

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.