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OverviewFull Product DetailsAuthor: Colin FyfePublisher: Springer London Ltd Imprint: Springer London Ltd Edition: Softcover reprint of hardcover 1st ed. 2005 Dimensions: Width: 15.50cm , Height: 2.10cm , Length: 23.50cm Weight: 0.617kg ISBN: 9781849969451ISBN 10: 1849969450 Pages: 383 Publication Date: 22 October 2010 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Out of stock  The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available. Table of ContentsSingle Stream Networks.- Background.- The Negative Feedback Network.- Peer-Inhibitory Neurons.- Multiple Cause Data.- Exploratory Data Analysis.- Topology Preserving Maps.- Maximum Likelihood Hebbian Learning.- Dual Stream Networks.- Two Neural Networks for Canonical Correlation Analysis.- Alternative Derivations of CCA Networks.- Kernel and Nonlinear Correlations.- Exploratory Correlation Analysis.- Multicollinearity and Partial Least Squares.- Twinned Principal Curves.- The Future.ReviewsFrom the reviews of the first edition: This book is concerned with developing unsupervised learning procedures and building self organizing network modules that can capture regularities of the environment. ... the book provides a detailed introduction to Hebbian learning and negative feedback neural networks and is suitable for self-study or instruction in an introductory course. (Nicolae S. Mera, Zentralblatt MATH, Vol. 1069, 2005) From the reviews of the first edition: This book is concerned with developing unsupervised learning procedures and building self organizing network modules that can capture regularities of the environment. ! the book provides a detailed introduction to Hebbian learning and negative feedback neural networks and is suitable for self-study or instruction in an introductory course. (Nicolae S. Mera, Zentralblatt MATH, Vol. 1069, 2005) "From the reviews of the first edition: ""This book is concerned with developing unsupervised learning procedures and building self organizing network modules that can capture regularities of the environment. ! the book provides a detailed introduction to Hebbian learning and negative feedback neural networks and is suitable for self-study or instruction in an introductory course."" (Nicolae S. Mera, Zentralblatt MATH, Vol. 1069, 2005)" Author InformationTab Content 6Author Website:Countries AvailableAll regions |
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