Presentation	2012-01-23 Dynamical properties of sparsely connected chaotic neural networks Kiyotaka Iguchi, Toshiya IWAI,
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Abstract(in English)	In the brain, many regions that are related to various functions are sparsely connected and transfer information between them. We numerically investigate correlation of dynamical states and information transmission between sparsely one-way connected auto-associated chaotic neural networks in imitation of real brain and found as follows: (i) as connection strength is larger, degree of chaos becomes weaker while correlation between networks becomes stronger, (ii) average mutual information between outputs of networks oscillate as time difference of outputs.
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Keyword(in English)	Chaotic Neural Network / information transmission / association
Paper #	NLP2011-124
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Committee	NLP
Conference Date	2012/1/16(1days)
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Registration To	Nonlinear Problems (NLP)
Language	JPN
Title (in Japanese)	(See Japanese page)
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Title (in English)	Dynamical properties of sparsely connected chaotic neural networks
Sub Title (in English)
Keyword(1)	Chaotic Neural Network
Keyword(2)	information transmission
Keyword(3)	association
1st Author's Name	Kiyotaka Iguchi
1st Author's Affiliation	Department of Computer Science, College of Engineering, Nihon University()
2nd Author's Name	Toshiya IWAI
2nd Author's Affiliation	Department of Computer Science, College of Engineering, Nihon University
Date	2012-01-23
Paper #	NLP2011-124
Volume (vol)	vol.111
Number (no)	395
Page	pp.pp.-
#Pages	6
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