An information theoretic approach to neural computing:

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 n...

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Bibliographic Details
Main Authors: Deco, Gustavo 1961- (Author), Obradovic, Dragan (Author)
Format: Book
Language:English
Published: New York [u.a.] Springer 1997
Edition:Corr. 2. printing
Series:Perspectives in neural computing
Subjects:
Summary: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 nonlinear independent component analysis, and Boltzmann machines. Readers are assumed to have a basic understanding of neural networks, but all of 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 book to be a very valuable contribution to this topic.
Physical Description:XIII, 261 S. graph. Darst.
ISBN:0387946667

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