Presentation	2001/3/10 Statistical Properties of Chaos Associative Memory MASAHIRO NAKAGAWA,
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Abstract(in English)	In this report we shall propose a chaos dynamic memory model applied to the chaotic autoassociation memory. The present artificial neuron model is properly characterized in terms of a time-dependent sinusoidal activation function to involve a transient chaotic dynamics as well as the energy steepest descent strategy. It is elucidated that the present neural network has a remarkable retrieval ability beyond the conventional models with 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 as well as the symmetry of the dynamics equation.
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Keyword(in English)	chaos neuron / associative memory / sinusoidal mapping
Paper #	NLP2000-176
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Conference Information
Committee	NLP
Conference Date	2001/3/10(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)	Statistical Properties of Chaos Associative Memory
Sub Title (in English)
Keyword(1)	chaos neuron
Keyword(2)	associative memory
Keyword(3)	sinusoidal mapping
1st Author's Name	MASAHIRO NAKAGAWA
1st Author's Affiliation	Nagaoka University of Technology()
Date	2001/3/10
Paper #	NLP2000-176
Volume (vol)	vol.100
Number (no)	681
Page	pp.pp.-
#Pages	8
Date of Issue