An Information-Theoretic Approach to Neural Computing (Perspectives in Neural Computing)
0387946667
9780387946665
Description:
A detailed formulation of neural networks from the information-theoretic viewpoint. The authors show how this perspective provides new insights into the design theory of neural networks. In particular they demonstrate 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 varied scientific disciplines, notably cognitive scientists, engineers, physicists, statisticians, and computer scientists, will find this an extremely valuable introduction to this topic.
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- An Information-Theoretic Approach to Neural Computing (Perspectives in Neural Computing)Deco, Gustavo; Obradovic, DraganEdition:Softcover reprint of the original 1st ed. 1996ISBN-13:9781461284697
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