Analysis of Topological Structure in Transiently Chaotic Neural Networks

被引：0

作者：

Yang GAO ^{[1
]}

Zuo-huan ZHENG ^{[1
]}

机构：

[1] Institute of Applied Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences

来源：

Acta Mathematicae Applicatae Sinica | 2018年 / 34卷 / 03期

基金：

中国国家自然科学基金;

关键词：

transiently chaotic neural networks; Li-Yorke chaos; no division;

D O I：

暂无

中图分类号：

TP183 [人工神经网络与计算];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Under the condition that the damping factor is between zero and one, chaotic dynamics is proved to exist in one-dimensional transiently chaotic neural networks by Li-Misiurewicz theorem. This result extends the previous result which is done under the condition that the damping factor is zero. Because the value of damping factor affects the speed of dynamical process of transiently chaotic neural networks, this result provides more complete theoretical basis for applications. Finally, two examples by numerical simulation are given to reinforce and illustrate this result.

引用

页码：610 / 621

页数：12

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