Models of Neural Networks III

Association, Generalization, and Representation

  • Eytan Domany
  • J. Leo van Hemmen
  • Klaus Schulten

Part of the Physics of Neural Networks book series (NEURAL NETWORKS)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Andreas V. M. Herz
    Pages 1-54
  3. Günther Palm, Friedrich T. Sommer
    Pages 79-118
  4. H.-O. Carmesin
    Pages 119-149
  5. Manfred Opper, Wolfgang Kinzel
    Pages 151-209
  6. David J. C. MacKay
    Pages 211-254
  7. I. Guyon, J. Bromley, N. Matić, M. Schenkel, H. Weissman
    Pages 255-279
  8. Kakali Sarkar, Klaus Schulten
    Pages 281-302
  9. Back Matter
    Pages 303-311

About this book


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.


algorithms artificial intelligence convergence cortex neural networks self-organizing map statistics training

Editors and affiliations

  • Eytan Domany
    • 1
  • J. Leo van Hemmen
    • 2
  • Klaus Schulten
    • 3
  1. 1.Department of ElectronicsWeizmann Institute of ScienceRehovotIsrael
  2. 2.Institut für Theoretische PhysikTechnische Universität MünchenGarching bei MünchenGermany
  3. 3.Department of Physics and Beckman InstituteUniversity of IllinoisUrbanaUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag New York, Inc. 1996
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4612-6882-6
  • Online ISBN 978-1-4612-0723-8
  • Series Print ISSN 0939-3145
  • Buy this book on publisher's site