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.
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页码：501 / 522
页数：21
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