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

L.C. Miranda and R. Riera

Physica A: Statistical Mechanics and its Applications, 1998, vol. 248, issue 3, 235-246

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.

Keywords: Neural networks (search for similar items in EconPapers)
Date: 1998
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:248:y:1998:i:3:p:235-246

DOI: 10.1016/S0378-4371(97)00499-8

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