Finite-time stability of the impulsive stochastic neural networks with delay

被引：0
|
作者：
Lu C.-T. [1 ]
Yu S. [1 ]
Cheng P. [1 ]
机构：
[1] School of Mathematical Sciences, Anhui University, Hefei, 230601, Anhui
来源：
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2020年 / 37卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Finite-time stability; Impulses; Linear matrix inequality; Lyapunov functional; Neural networks;
D O I：
10.7641/CTA.2019.90102
中图分类号：
学科分类号：
摘要：
This paper focuses on the problem of finite-time stability of the impulsive stochastic neural networks with delay. Three types of impulses are considered: the impulses are input disturbances, the impulses are neutral type and the impulses are stabilizing. For each type of impulses, by using Lyapunov functional and linear matrix inequalities (LMIs) techniques combined with the concept of the average impulsive interval, the sufficient conditions for the mean square finitetime stability are established in terms of matrix inequalities. Finally, a numerical example is given to verify the effectiveness of the theoretical results. © 2020, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.
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页码：187 / 192
页数：5
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