Dynamics of associative memory with a self-consistent noise

Research output: Contribution to conferencePaper

Abstract

The Glauber dynamics of magnetic systems has been extended to the case of neural networks with a general odd response function. We have derived a set of recursion relations for the overlap parameter, noise average and noise variance taken as macrovariables of the process describing the dynamics of associative memory. The retrieval process has been studied then for a hyperbolic tangent transfer function by the self-consistent signal to noise ratio method. It has been taken into account the fatigue effect of the real neuron. The phase diagrams of the retrieval process reveals an enhanced storage capacity for a certain set of parameter values.

Original languageEnglish (US)
Pages162-170
Number of pages9
StatePublished - Jan 1 1995
Externally publishedYes
EventProceedings of the 5th IEEE Workshop on Neural Networks for Signal Processing (NNSP'95) - Cambridge, MA, USA
Duration: Aug 31 1995Sep 2 1995

Other

OtherProceedings of the 5th IEEE Workshop on Neural Networks for Signal Processing (NNSP'95)
CityCambridge, MA, USA
Period8/31/959/2/95

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ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Software

Cite this

Opris, I. (1995). Dynamics of associative memory with a self-consistent noise. 162-170. Paper presented at Proceedings of the 5th IEEE Workshop on Neural Networks for Signal Processing (NNSP'95), Cambridge, MA, USA, .