Neural Networks

Regularized Radial Basis Function Networks: Theory and Applications

Name: Regularized Radial Basis Function Networks: Theory and Applications
Author: Paul Yee
ISBN: 9780471353492

by Paul Yee, Simon Haykin

Available on Bookshop Write a review

Books.org participates in affiliate programs including Bookshop.org and the Amazon Services LLC Associates Program. We may earn a commission from qualifying purchases made through links on this page, at no additional cost to you.

Overview

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.

Synopsis

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.

SciTech Book News

To serve as a bridge between nonparametric estimation and artificial neural networks, Yee...and Haykin...examines the interplay of ides in the two ideas.

Reviews

There are no reviews yet. Log in to write one.

Editorials

From the Publisher

"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)

SciTech Book News

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

To serve as a bridge between nonparametric estimation and artificial neural networks, Yee...and Haykin...examines the interplay of ides in the two ideas.

Booknews

To serve as a bridge between nonparametric estimation and artificial neural networks, Yee, in the private sector, and Haykin (McMasters U.) examines the interplay of ideas in the two ideas. The specific vehicle for their study is the regularized strict interpolation radial basis function estimate or neural network, one of the better known kernel- based methods for estimation and function approximation. Their target readers are researchers, practitioners, and graduate students in engineering and the sciences. Annotation c. Book News, Inc., Portland, OR (booknews.com)