Information-Theoretic Approach to Neural Computing

Name: Information-Theoretic Approach to Neural Computing
Brand: Springer-Verlag New York Inc.
SKU: 9781461284697
Price: 2286 CZK
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Autor: Gustavo Deco, Dragan Obradovic

Jazyk:

Vazba: Brožovaná

Vydavatel: Springer-Verlag New York Inc.

Dostupnost: Skladem u dodavatele

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2 286 Kč

A detailed formulation of neural networks from the information-theoretic viewpoint. The authors show...

Informace o knize

Autor

Gustavo Deco, Dragan Obradovic

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2011

Stránek

262

EAN

9781461284697

ISBN

1461284694

Enbook ID

06795673

Vydavatel

Springer-Verlag New York Inc.

Hmotnost

429

Rozměry

155 x 235 x 16

Kompletní popis

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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Information-Theoretic Approach to Neural Computing

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