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Models of Neural Networks III: Association, Generalization, and Representation

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Models of Neural Networks III: Association, Generalization, and Representation - Domany, Eytan (Editor), and Hemmen, J. Leo van (Editor), and Schulten, Klaus (Editor)
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One of the most challenging and fascinating problems of the theory of neural nets is that of asymptotic behavior, of how a system behaves as time proceeds. This is of particular relevance to many practical applications. Here we focus on association, generalization, and representation. We turn to the last topic first. The introductory chapter, "Global Analysis of Recurrent Neural Net works," by Andreas Herz presents an in-depth analysis of how to construct a Lyapunov function for various types of dynamics and neural coding. ...

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Models of Neural Networks III: Association, Generalization, and Representation 2012, Springer-Verlag New York Inc., New York, NY

ISBN-13: 9781461268826

Paperback

Models of Neural Networks III: Association, Generalization, and Representation 1995, Springer, New York, NY

ISBN-13: 9780387943688

1996 edition

Hardcover