DYNAMICS IN A CLASS OF NEURON MODELS

被引：0
|
作者：
Wang Junping (Dept. of Math. and Physics
机构：
来源：
Annals of Applied Mathematics | 2009年 / 01期
关键词：
discrete-time neuron model; periodic activation function; periodic-doubling bifurcation; anti-integrable limit method; chaos;
D O I：
暂无
中图分类号：
O175 [微分方程、积分方程];
学科分类号：
070104 ;
摘要：
In this paper, we investigate the dynamics in a class of discrete-time neuron mod-els. The neuron model we discussed, defined by such periodic input-output mapping as a sinusoidal function, has a remarkably larger memory capacity than the conven-tional association system with the monotonous function. Our results show that the orbit of the model takes a conventional bifurcation route, from stable equilibrium, to periodicity, even to chaotic region. And the theoretical analysis is verified by numerical simulations.
引用
收藏
页码：67 / 73
页数：7
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