Finite-time stability of fractional-order bidirectional associative memory neural networks with mixed time-varying delays

被引：0

作者：

Zhanying Yang

Jie Zhang

Yanqing Niu

机构：

[1] South-Central University for Nationalities,School of Mathematics and Statistics

来源：

Journal of Applied Mathematics and Computing | 2020年 / 63卷

关键词：

Fractional-order system; Bidirectional associative memory neural networks; Finite-time stability; Mixed time-varying delays; 34D20; 34K37; 92B20;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

This paper investigates the finite-time stability of fractional-order bidirectional associative memory neural networks with mixed time-varying delays. The sufficient conditions are derived to ensure the finite-time stability of systems by employing some analytical techniques and some inequalities. In addition, some conditions are achieved to guarantee the existence, the uniqueness and the finite-time stability of equilibrium point. Finally, two numerical examples are given to verify the effectiveness of the obtained main results.

引用

页码：501 / 522

页数：21

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