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Recalling properties of non-random patterns in neural networks A Monte-Carlo study

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  • Miranda, L.C.
  • Riera, R.

Abstract

We introduce a neural network with the ability of recalling p non-random patterns displaying a hierarchical distribution of activities for all p⩽N − 1, N being the number of neurons. The stability of the retrieval states is studied as a function of temperature T and α = p/N. The temperature below which the patterns are retrievable states has been determined by computer simulations. The features of the memory stability are related to a weak correlation of the synaptic efficacy distribution.

Suggested Citation

  • Miranda, L.C. & Riera, R., 1998. "Recalling properties of non-random patterns in neural networks A Monte-Carlo study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 248(3), pages 235-246.
    • Handle: RePEc:eee:phsmap:v:248:y:1998:i:3:p:235-246
    DOI: 10.1016/S0378-4371(97)00499-8
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    Keywords

    Neural networks;

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