Presentation 1998/3/13
Chaos Associative Memory with a Periodic Activation Function
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In this paper we shall propose a novel chaos neural network model applied to the chaotic autoassociation memory. The present artificial neuron model is properly characterized in terms of a time-dependent periodic activation function to involve a chaotic dynamics as well as the energy steepest descent strategy. It is elucidated that the present neural network has a remarkable ability of the dynamic memory retrievals beyond the conventional models with the nonmonotonous activation function as well as such a monotonous activation function as sigmoidal one. This advantage is found to result from the property of the analogue periodic mapping accompanied with a chaotic behaviour of the neurons. It is also concluded that present analogue neuron model with the periodicity control has an apparently large memory capacity in comparison with the previously proposed association models.
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Keyword(in English) chaos neuron / periodic mapping / associative memory
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Conference Information
Committee NLP
Conference Date 1998/3/13(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Chaos Associative Memory with a Periodic Activation Function
Sub Title (in English)
Keyword(1) chaos neuron
Keyword(2) periodic mapping
Keyword(3) associative memory
1st Author's Affiliation Nagaoka University of Technology()
Date 1998/3/13
Paper #
Volume (vol) vol.97
Number (no) 592
Page pp.pp.-
#Pages 8
Date of Issue