Random perturbations to hebbian synapses of associative memory using a genetic algorithm

Akira Imada, Keijiro Araki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

We apply evolutionary algorithms to Hopfield model of associative memory. Previously we reported that. a genetic algorithm using ternary chromosomes evolves the Hebb-rule associative memory to enhance its storage capacity by pruning some connections. This paper describes a genetic algorithm using real- encoded chromosomes which successfully evolves over-loaded Hebbian synaptic weights to function as an associative memory. The goal of this study is to shed new light on the analysis of the Hopfield model, which also enables us to use the model as more challenging test suite for evolutionary computations.

Original languageEnglish
Title of host publicationBiological and Artificial Computation
Subtitle of host publicationFrom Neuroscience to Technology - International Work-Conference on Artificial and Natural Neural Networks, IWANN 1997, Proceedings
PublisherSpringer Verlag
Pages398-407
Number of pages10
ISBN (Print)3540630473, 9783540630470
DOIs
Publication statusPublished - 1997
Event4th International Work-Conference on Artificial and Natural Neural Networks, IWANN 1997 - Lanzarote, Canary Islands, Spain
Duration: Jun 4 1997Jun 6 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1240 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other4th International Work-Conference on Artificial and Natural Neural Networks, IWANN 1997
CountrySpain
CityLanzarote, Canary Islands
Period6/4/976/6/97

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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