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Regularized Radial Basis Function Networks Paul V. Yee (PMC-Sierra, Inc.)

Regularized Radial Basis Function Networks By Paul V. Yee (PMC-Sierra, Inc.)

Summary

This title deals with the design of Radial Basis Function Networks (RBFNs), one of two classes of feedforward networks with applications in artificial neural networks, for particular tasks. These applications are in such engineering problems as nonlinear process estimation and control.

Regularized Radial Basis Function Networks Summary

Regularized Radial Basis Function Networks: Theory and Applications by Paul V. Yee (PMC-Sierra, Inc.)

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.

Regularized Radial Basis Function Networks Reviews

"To serve as a bridge between nonparametric estimation and artificial neural networks, Yee...and Haykin...examines the interplay of ides in the two ideas." (SciTech Book News Vol. 25, No. 2 June 2001)

About Paul V. Yee (PMC-Sierra, Inc.)

Paul V. Yee is the author of Regularized Radial Basis Function Networks: Theory and Applications, published by Wiley.

Simon Haykin is the author of Regularized Radial Basis Function Networks: Theory and Applications, published by Wiley.

Table of Contents

Preface.

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.

Additional information

NPB9780471353492
9780471353492
0471353493
Regularized Radial Basis Function Networks: Theory and Applications by Paul V. Yee (PMC-Sierra, Inc.)
New
Hardback
John Wiley & Sons Inc
2001-04-24
208
N/A
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