Regularized Radial Basis Function Networks
Theory and Applications
Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control
1. Edition April 2001
XVI, 192 Pages, Hardcover
Wiley & Sons Ltd
Short Description
Artificial Neural Networks are an important area of research and there are many practical applications. The Radial Basis Function Network is one of two classes of feedforward networks with applications in artificial neural networks. These applications are in such engineering problems as nonlinear process estimation and control. The present book deals with the design of RBFNs for particular tasks.
Simon Haykin is a well-known author of books on neural networks.
* An authoritative book dealing with cutting edge technology.
* This book has no competition.
Notations.
Introduction.
Basic Tools.
Probability Estimation and Pattern Classification.
Nonlinear Time-Series Prediction.
Nonlinear State Estimation.
Dynamic Reconstruction of Chaotic Processes.
Discussion.
Appendix of Notes to the Text.
References.
Index.
