Models of Neural Networks III: Association, Generalization, and Representation - Couverture souple

Couverture souple

ISBN 10 : 1461268826 ISBN 13 : 9781461268826

Editeur : Springer, 2012

Synopsis

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. It includes a review of the recent work with John Hopfield on integrate-and- fire neurons with local interactions. The chapter, "Receptive Fields and Maps in the Visual Cortex: Models of Ocular Dominance and Orientation Columns" by Ken Miller, explains how the primary visual cortex may asymptotically gain its specific structure through a self-organization process based on Hebbian learning. His argu- ment since has been shown to be rather susceptible to generalization.

A propos du livre

Présentation de l'éditeur

This collection of articles by leading researchers in neural networks responds to the urgent need for timely and comprehensive reviews in a multidisciplinary, rapidly developing field of research. It continues the themes of the previous volume, but shifts its focus to more practical matters, such as data storage and retrieval, and the recognition of handwriting.

Détails de l'édition

• Éditeur: Springer
• Date d'édition: 2012
• Langue: anglais
• ISBN 10: 1461268826
• ISBN 13: 9781461268826
• Reliure: Broché
• Nombre de pages: 328
• Éditeur: Domany Eytan, Hemmen J. Leo Van, Schulten Klaus
• Coordonnées du fabricant: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Allemagne