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OverviewFull Product DetailsAuthor: Gustavo Deco , Dragan ObradovicPublisher: Springer-Verlag New York Inc. Imprint: Springer-Verlag New York Inc. Edition: 1st ed. 1996. Corr. 2nd printing 1997 Dimensions: Width: 15.50cm , Height: 1.70cm , Length: 23.50cm Weight: 1.270kg ISBN: 9780387946665ISBN 10: 0387946667 Pages: 262 Publication Date: 08 February 1996 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of Contents1 Introduction.- 2 Preliminaries of Information Theory and Neural Networks.- 2.1 Elements of Information Theory.- 2.2 Elements of the Theory of Neural Networks.- I: Unsupervised Learning.- 3 Linear Feature Extraction: Infomax Principle.- 4 Independent Component Analysis: General Formulation and Linear Case.- 5 Nonlinear Feature Extraction: Boolean Stochastic Networks.- 6 Nonlinear Feature Extraction: Deterministic Neural Networks.- II: Supervised Learning.- 7 Supervised Learning and Statistical Estimation.- 8 Statistical Physics Theory of Supervised Learning and Generalization.- 9 Composite Networks.- 10 Information Theory Based Regularizing Methods.- References.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |