A Study of Association Model with Periodic Chaos Neurons
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概要
- 論文の詳細を見る
In this work a chaotic neuron model with a periodic activation function is proposed and applied to an autoassociation problem. It is elucidated that the presently found chaotic behavior may be controlled in terms of a single parameter corresponding to the periodicity of the periodic mapping. It is found that the present autoassociation model may associate more effectively an embedded pattern than the conventional association model with a monotonous step function as an activation function as seen in the Associatron. In addition it is also found that the association may be accomplished even though the multiple gray levels as the embedded patterns are concerned, and that the association rate may not be reduced below 0.05 even for such cases.
- 社団法人日本物理学会の論文
- 1995-12-15
著者
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Nakagawa Masahiro
Department Of Electrical Engineering Faculty Of Engineering Nagaoka University Of Technology
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Nakagawa Masahiro
Deparment Of Electrical Engineering Faculty Of Engineering Nagaoka University Of Technology
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Kasahara Tsuyoshi
Department of Electrical Engineering, Faculty of Engineering, Nagaoka University of Technology
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Kasahara T
Department Of Electrical Engineering Faculty Of Engineering Nagaoka University Of Technology
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