An Information-theoretic Approach to Neural Computing (Perspectives in Neural Computing)

Gustavo Deco

ISBN 10: 1461284694 / ISBN 13: 9781461284697

Published by Springer New York, 2012

About this Item

reprint edition. 261 pages. 9.25x6.10x0.60 inches. In Stock.

Seller Inventory # x-1461284694

Bibliographic Details

• Title: An Information-theoretic Approach to Neural Computing (Perspectives in Neural Computing)
• Publisher: Springer New York
• Publication Date: 2012
• Language: English
• ISBN 10: 1461284694
• ISBN 13: 9781461284697
• Binding: Paperback
• Condition: Brand New
• Weight: 0.4 kilograms

About this title

Synopsis

Neural networks provide a powerful new technology to model and control nonlinear and complex systems. In this book, the authors present a detailed formulation of neural networks from the information-theoretic viewpoint. They show how this perspective provides new insights into the design theory of neural networks. In particular they show how these methods may be applied to the topics of supervised and unsupervised learning including feature extraction, linear and non-linear independent component analysis, and Boltzmann machines. Readers are assumed to have a basic understanding of neural networks, but all the relevant concepts from information theory are carefully introduced and explained. Consequently, readers from several different scientific disciplines, notably cognitive scientists, engineers, physicists, statisticians, and computer scientists, will find this to be a very valuable introduction to this topic.