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Hokkaido University Preprint Series in Mathematics >
A new type of self-organization associated with chaotic dynamics in neural networks
| Title: | A new type of self-organization associated with chaotic dynamics in neural networks |
| Authors: | Tsuda, I. Browse this author |
| Issue Date: | 1-May-1996 |
| Publisher: | Department of Mathematics, Hokkaido University |
| Journal Title: | Hokkaido University Preprint Series in Mathematics |
| Volume: | 337 |
| Start Page: | 1 |
| End Page: | 16 |
| Abstract: | 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. |
| Type: | bulletin (article) |
| URI: | http://hdl.handle.net/2115/69087 |
| Appears in Collections: | 理学院・理学研究院 (Graduate School of Science / Faculty of Science) > Hokkaido University Preprint Series in Mathematics
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Submitter: 数学紀要登録作業用
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