A new type of self-organization associated with chaotic dynamics in neural networks

Tsuda, I.

Hokkaido University Preprint Series in Mathematics, 1996, 337, 1-16

Permalink : https://doi.org/10.14943/83483

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アクセス権	open access
DOI	https://doi.org/10.14943/83483
URI	https://hdl.handle.net/2115/69087
タイトル	A new type of self-organization associated with chaotic dynamics in neural networks
著者	著者名 Tsuda, I.
言語	英語
発行日	1996-05-01
出版者	Department of Mathematics, Hokkaido University
収録物名	Hokkaido University Preprint Series in Mathematics
巻(号)	337
ページ	1-16
抄録	A new type of self-organized dynamics is presented, in relation with chaos in neural networks. One is chaotic itinerancy and the other is chaos-driven contraction dynamics. The former is addressed as a universal behavior in high-dimensional dynamical systems. In particuiar, it can be viewed as one possible form of memory dynamics in brain. The latter gives rise to singular-continuous nowhere-differentiable attractors. These dynamics can be related to each other in the context of dimentionality and of chaotic information processings. Possible roles of these oomplex dynamics in brain are also discussed.
資源タイプ	紀要論文
出版タイプ	Version of Record