Information Theoretic Neural Computation

By: Ryotaro Kamimura

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Hardcover | 23 December 2002

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220 Pages

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23.5 x 15.88 x 1.91

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In order to develop new types of information media and technology, it is essential to model complex and flexible information processing in living systems. This text presents an approach to modelling complex information processing in living systems. Traditional information-theoretic methods in neural networks are unified in one framework, in other words, alpha-entropy. This approach should enable information systems such as computers to imitate and simulate human complex behaviour and to uncover the deepest secrets of the human mind.

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You Can Find This Book In

Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Neural Networks & Fuzzy Systems Reference, Information & Interdisciplinary Subjects Research & Information Information theory Booktopia Publisher Services World Scientific Publishing

Preface
Introduction	p. 1
Information in Neural Networks	p. 5
Information Minimization	p. 17
Information Maximization	p. 31
Constrained Information Maximization	p. 57
Neural Feature Detectors	p. 73
Information Maximization and Minimization	p. 99
Information Controller	p. 127
Information Control by [alpha]-Entropy	p. 157
Integrated Information Processing Systems	p. 175
Data Description	p. 191
Sonority	p. 195
Bibliography	p. 197
Index	p. 205
Table of Contents provided by Blackwell. All Rights Reserved.

Information Theoretic Neural Computation

At a Glance

Hardcover

Shipping

How to return your order

Defective items

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