HUSCAP logo Hokkaido Univ. logo

Hokkaido University Collection of Scholarly and Academic Papers >
Graduate School of Science / Faculty of Science >
Hokkaido University Preprint Series in Mathematics >

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

Files in This Item:
pre337.pdf1.08 MBPDFView/Open
Please use this identifier to cite or link to this item:http://doi.org/10.14943/83483

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
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

Submitter: 数学紀要登録作業用

Export metadata:

OAI-PMH ( junii2 , jpcoar )


 

Feedback - Hokkaido University