Searching real-valued synaptic weights of hopfield's associative memory using evolutionary programming

Akira Imada, Keijiro Araki

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

1 Citation (Scopus)

Abstract

We apply evolutionary computations to Hopfield model of associative memory. Although there have been a lot of researches which apply evolutionary techniques to layered neural networks, their applications to Hopfield neural networks remain few so far. Previously we reported that a genetic Mgorithm using discrete encoding chromosomes evolves the Hehb-rule associative memory to enhance its storage capacity. We also reported that the genetic algorithm evolves a network with random synaptic weights eventually to store some number of patterns as fixed points. In this paper we present an evolution of the Hopfield model of associative memory using evolutionary programming as a reM-valued parameter optimization.

Original languageEnglish
Title of host publicationEvolutionary Programming VI - 6th International Conference, EP 1997, Proceedings
PublisherSpringer Verlag
Pages13-22
Number of pages10
Volume1213
ISBN (Print)9783540627883
DOIs
Publication statusPublished - 1997
Event6th International Conference on Evolutionary Programming, EP 1997 - Indianapolis, United States
Duration: Apr 13 1997Apr 16 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1213
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other6th International Conference on Evolutionary Programming, EP 1997
CountryUnited States
CityIndianapolis
Period4/13/974/16/97

Fingerprint

Evolutionary Programming
Associative Memory
Evolutionary algorithms
Hopfield Model
Data storage equipment
Neural Network Applications
Hopfield neural networks
Hopfield Neural Network
Storage Capacity
Parameter Optimization
Evolutionary Computation
Chromosomes
Chromosome
Encoding
Genetic algorithms
Fixed point
Genetic Algorithm
Neural networks

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Imada, A., & Araki, K. (1997). Searching real-valued synaptic weights of hopfield's associative memory using evolutionary programming. In Evolutionary Programming VI - 6th International Conference, EP 1997, Proceedings (Vol. 1213, pp. 13-22). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1213). Springer Verlag. https://doi.org/10.1007/BFb0032342

Searching real-valued synaptic weights of hopfield's associative memory using evolutionary programming. / Imada, Akira; Araki, Keijiro.

Evolutionary Programming VI - 6th International Conference, EP 1997, Proceedings. Vol. 1213 Springer Verlag, 1997. p. 13-22 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1213).

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

Imada, A & Araki, K 1997, Searching real-valued synaptic weights of hopfield's associative memory using evolutionary programming. in Evolutionary Programming VI - 6th International Conference, EP 1997, Proceedings. vol. 1213, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1213, Springer Verlag, pp. 13-22, 6th International Conference on Evolutionary Programming, EP 1997 , Indianapolis, United States, 4/13/97. https://doi.org/10.1007/BFb0032342
Imada A, Araki K. Searching real-valued synaptic weights of hopfield's associative memory using evolutionary programming. In Evolutionary Programming VI - 6th International Conference, EP 1997, Proceedings. Vol. 1213. Springer Verlag. 1997. p. 13-22. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/BFb0032342
Imada, Akira ; Araki, Keijiro. / Searching real-valued synaptic weights of hopfield's associative memory using evolutionary programming. Evolutionary Programming VI - 6th International Conference, EP 1997, Proceedings. Vol. 1213 Springer Verlag, 1997. pp. 13-22 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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