Critical Phenomenon in a Neural Network Model : A Localization-Delocalization Transition of Excited Clusters
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概要
- 論文の詳細を見る
Numerical study is done on a critical phenomenon in a neural network model of the McCulloch-Pitts type. Such a net, one of excitable media, consists of "neurons" (binary decision elements) each of which randomly sits on a square lattice and is connected to its four neighbors. When the net is activated locally, the "fire" spreads over from the origin according to the deterministic rule. After transient, a self-sustained mode of excitation (time-periodic firing pattern) is established. It is found that a size of the largest excitation tends to diverge as the excitability of the net is increased (a localization-delocalization transition). Numerically evaluated power-law exponents suggest that the criticality of such transition belongs to the same universality class of the percolation transition.
- 社団法人日本物理学会の論文
- 1993-01-15
著者
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Satoh Kazuhiko
Department Of Physics Faculty Of Science Saitama University
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OKABE Yutaka
Department of Physics,Tohoku University
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Okabe Y
Tokyo Metropolitan Univ. Tokyo
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Okabe Yutaka
R&d Group Oki Electric Industry Co. Ltd.
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Okabe Yutaka
Department Of Applied Chemistry Science And Engineering Waseda University
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Satoh K
Department Of Physics Faculty Of Science Saitama University
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Satoh Kazuhiro
Department of Physics, Faculty of Science, Tohoku University
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Satoh Kazuhiro
Department Of Applied Physics And Chemistry The University Of Electro-communications
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Okabe Yutaka
Department Of Pure And Applied Sciences Universtiy Of Tokyo
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Satoh Kazuhiro
Department of Physics, Faculty of Science, Saitama University
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