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Neural Networks and Learning Machines Hardcover - 2007
by Simon Haykin
From the rear cover
Neural Networks and Learning Machines
Third Edition Simon Haykin McMaster University, Canada This third edition of a classic book presents a comprehensive treatment of neural networks and learning machines. These two pillars that are closely related. The book has been revised extensively to provide an up-to-date treatment of a subject that is continually growing in importance. Distinctive features of the book include: - On-line learning algorithms rooted in stochastic gradient descent; small-scale and large-scale learning problems. - Kernel methods, including support vector machines, and the representer theorem. - Information-theoretic learning models, including copulas, independent components analysis (ICA), coherent ICA, and information bottleneck. - Stochastic dynamic programming, including approximate and neurodynamic procedures. - Sequential state-estimation algorithms, including Kalman and particle filters. - Recurrent neural networks trained using sequential-state estimation algorithms. - Insightful computer-oriented experiments. Just as importantly, the book is written in a readable style that is Simon Haykin's hallmark.Details
- Title Neural Networks and Learning Machines
- Author Simon Haykin
- Binding Hardcover
- Edition INTERNATIONAL ED
- Pages 936
- Volumes 1
- Language ENG
- Publisher Pearson, China
- Date May 1, 2007
- Illustrated Yes
- Features Bibliography, Glossary, Illustrated, Index, Table of Contents
- ISBN 9780131471399 / 0131471392
- Weight 3.6 lbs (1.63 kg)
- Dimensions 9.2 x 7.2 x 2.1 in (23.37 x 18.29 x 5.33 cm)
- Library of Congress subjects Neural networks (Computer science), Adaptive filters
- Library of Congress Catalog Number 2008034079
- Dewey Decimal Code 006.32
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New York: Pearson, 2009. Third Edition. Hardcover. Fine. xxx, 906 p. 24 cm. Numerous figures. Black and red text. Hardcover.
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Neural Networks and Learning Machines (3rd Edition)
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