Chaotic multidirectional associative memory

Y. Osana, M. Hattori, M. Hagiwara

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

8 Citations (Scopus)

Abstract

A chaotic multidirectional associative memory (CMAM) is proposed and simulated. It can deal with many-to-many associations and the structure is very simple. Furthermore, similarity to a psychological fact (priming effect) is observed in the association of the CMAM. In order to enable many-to-many associations, the CMAM memorizes each training data together with its own contextual information and employs chaotic neurons. Since the chaotic neurons change their states by chaos, many-to-many associations can be realized in the CMAM.

Original languageEnglish
Title of host publication1997 IEEE International Conference on Neural Networks, ICNN 1997
Pages1210-1215
Number of pages6
DOIs
Publication statusPublished - 1997
Event1997 IEEE International Conference on Neural Networks, ICNN 1997 - Houston, TX, United States
Duration: 1997 Jun 91997 Jun 12

Publication series

NameIEEE International Conference on Neural Networks - Conference Proceedings
Volume2
ISSN (Print)1098-7576

Conference

Conference1997 IEEE International Conference on Neural Networks, ICNN 1997
Country/TerritoryUnited States
CityHouston, TX
Period97/6/997/6/12

ASJC Scopus subject areas

  • Software

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