Presentation	1998/3/13 Chaos Associative Memory with a Periodic Activation Function MASAHIRO NAKAGAWA,
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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.
Keyword(in Japanese)	(See Japanese page)
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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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 Name	MASAHIRO NAKAGAWA
1st Author's Affiliation	Nagaoka University of Technology()
Date	1998/3/13
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Volume (vol)	vol.97
Number (no)	592
Page	pp.pp.-
#Pages	8
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