An Information-Theoretic Approach to Neural Computing

An Information-Theoretic Approach to Neural Computing
Author :
Publisher : Springer Science & Business Media
Total Pages : 288
Release :
ISBN-10 : 0387946667
ISBN-13 : 9780387946665
Rating : 4/5 (665 Downloads)

Book Synopsis An Information-Theoretic Approach to Neural Computing by : Gustavo Deco

Download or read book An Information-Theoretic Approach to Neural Computing written by Gustavo Deco and published by Springer Science & Business Media. This book was released on 1996-02-08 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


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