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Asymmetrically Diluted Neural Networks

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Models of Neural Networks I

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

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Synopsis

We review the properties of an exactly solvable model for an asymmetric neural network which is strongly diluted. We discuss in detail why the model can be solved exactly and derive its explicit solution in the framework of a new formalism for the dynamics of Ising spins. Results are presented for the static retrieval properties, time-dependent correlations and the distribution of neural activities.

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Authors
  1. Reiner Kree
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  2. Annette Zippelius
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Editor information

Editors and Affiliations

  1. Department of Electronics, Weizmann Institute of Science, 76100, Rehovot, Israel

    Eytan Domany

  2. Institut für Theoretische Physik, Technische Universität München, D-85747, Garching bei München, Germany

    J. Leo van Hemmen

  3. Department of Physics and Beckman Institute, University of Illinois, Urbana, IL, 61801, USA

    Klaus Schulten

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© 1995 Springer-Verlag Berlin Heidelberg

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Kree, R., Zippelius, A. (1995). Asymmetrically Diluted Neural Networks. In: Domany, E., van Hemmen, J.L., Schulten, K. (eds) Models of Neural Networks I. Physics of Neural Networks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79814-6_6

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  • DOI: https://doi.org/10.1007/978-3-642-79814-6_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-79816-0

  • Online ISBN: 978-3-642-79814-6

  • eBook Packages: Springer Book Archive

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