Presentation	2000/6/16 NLP2000-46 / NC2000-40 A Chaos Memory Retrieval with a Skew-Tent Activation Function Masahiro Nakagawa,
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Abstract(in English)	In this report we shall propose a chaos neural network model applied to the chaotic autoassociation memory. The present artificial neuron model is properly characerized in terms of a time-dependent skew-tent 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 the 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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Paper #	NLP2000-46,NC2000-40
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Committee	NLP
Conference Date	2000/6/16(1days)
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Registration To	Nonlinear Problems (NLP)
Language	ENG
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Title (in English)	NLP2000-46 / NC2000-40 A Chaos Memory Retrieval with a Skew-Tent Activation Function
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1st Author's Name	Masahiro Nakagawa
1st Author's Affiliation	Nagaoka University of Technology()
Date	2000/6/16
Paper #	NLP2000-46,NC2000-40
Volume (vol)	vol.100
Number (no)	125
Page	pp.pp.-
#Pages	8
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