A synergetic neural network with cross-correlation dynamics

In this paper, a cross‐correlation type synergetic neural network is proposed that realizes a perfect association. This model enables perfect association by incorporating synergetic dynamics into a conventional cross‐correlation type association memory model. The association sequence is determined b...

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Bibliographic Details
Published in:Electronics & communications in Japan. Part 3, Fundamental electronic science Fundamental electronic science, 1998-09, Vol.81 (9), p.37-47
Main Authors: Kitahara, Jun, Nakagawa, Masahiro
Format: Article
Language:English
Subjects:
chaos
cross-correlation type association model
order parameters
synergetic
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Summary:In this paper, a cross‐correlation type synergetic neural network is proposed that realizes a perfect association. This model enables perfect association by incorporating synergetic dynamics into a conventional cross‐correlation type association memory model. The association sequence is determined by the value of the product of the initial order parameters for an input pattern. Furthermore, we report on the usefulness of introducing chaotic fluctuations from the point of view of applications of this model to the time series configuration of many patterns and the time reduction needed for association. © 1998 Scripta Technica, Electron Comm Jpn Pt 3, 81(9): 37–47, 1998
ISSN:1042-0967
1520-6440
DOI:10.1002/(SICI)1520-6440(199809)81:9<37::AID-ECJC5>3.0.CO;2-W