What does the landscape of a hopfield associative memory look like?

Akira Imada, Keijiro Araki

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

1 Citation (Scopus)

Abstract

We apply evolutionary computations to the Hopfield's neural network model of associative memory. In the model, some of the appropriate configurations of synaptic weights giv e the network a function of associative memory. One of our goals is to obtain the distribution of these configurations in the synaptic weight space. In other words, our aim is to learn a geometry of a fitness landscape defined on the space. For the purpose, we use evolutionary walks to explore the fitness landscape in this paper.

Original languageEnglish
Title of host publicationEvolutionary Programming VII - 7th International Conference, EP 1998, Proceedings
EditorsV.W. Porto, N. Saravanan, D. Waagen, A.E. Eiben
PublisherSpringer Verlag
Pages647-656
Number of pages10
ISBN (Print)3540648917, 9783540648918
DOIs
Publication statusPublished - 1998
Event7th Annual Conference on Evolutionary Programming, EP 1998 - San Diego, United States
Duration: Mar 25 1998Mar 27 1998

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1447
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th Annual Conference on Evolutionary Programming, EP 1998
CountryUnited States
CitySan Diego
Period3/25/983/27/98

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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