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Freezing transition in asymmetric random neural networks with deterministic dynamics

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Zeitschrift für Physik B Condensed Matter

Abstract

A network of binary elements (spins, neurons) which are completely connected by random couplings is investigated for a deterministic dynamics. For general values of the symmetry parameter η extensive numerical simulations have been performed. With increasing symetry η a sharp transition from a chaotic motion to a frozen state is found.

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Authors and Affiliations

  1. Institut für Theoretische Physik, Justus-Liebig-Universität Giessen, Heinrich-Buff-Ring 16, D-6300, Giessen, Federal Republic of Germany

    Peter Spitzner & Wolfgang Kinzel

Authors
  1. Peter Spitzner
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  2. Wolfgang Kinzel
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Spitzner, P., Kinzel, W. Freezing transition in asymmetric random neural networks with deterministic dynamics. Z. Physik B - Condensed Matter 77, 511–517 (1989). https://doi.org/10.1007/BF01453802

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  • DOI: https://doi.org/10.1007/BF01453802

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