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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 help the reader grasp the underlying theory. This is a valuable reference for scientists and engineers working in mathematics, computer science, control or other fields related to information processing. It can also be used as a textbook for graduate courses in applied mathematics, computer science, automatic control and electrical engineering.
Contents:
- Fuzzy Neural Networks for Storing and Classifying
- Fuzzy Associative Memory — Feedback Networks
- Regular Fuzzy Neural Networks
- Polygonal Fuzzy Neural Networks
- Approximation Analysis of Fuzzy Systems
- Stochastic Fuzzy Systems and Approximations
- Application of FNN to Image Restoration
Readership: Scientists, engineers and graduate students in applied mathematics, computer science, automatic control and information processing.
