Tsuda I
Department of Mathematics, Graduate School of Science, Hokkaido University, Sappro, Japan.
Int J Neural Syst. 1996 Sep;7(4):451-9. doi: 10.1142/s0129065796000439.
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 particular, 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 dimensionality and of chaotic information processings. Possible roles of these complex dynamics in brain are also discussed.
提出了一种与神经网络中的混沌相关的新型自组织动力学。一种是混沌游走，另一种是混沌驱动的收缩动力学。前者被认为是高维动力系统中的一种普遍行为。特别地，它可以被视为大脑中记忆动力学的一种可能形式。后者产生奇异连续且处处不可微的吸引子。这些动力学在维度和混沌信息处理的背景下可以相互关联。还讨论了这些复杂动力学在大脑中的可能作用。
