New Criteria for Global Exponential Stability of Discrete-Time High-Order Neural Networks with Time-Varying Delays

被引：0
|
作者：
Dong, Zeyu [1 ]
Yang, Xin [1 ]
Zhang, Xian [1 ,2 ]
Wang, Xin [1 ,2 ]
机构：
[1] Heilongjiang Univ, Sch Math Sci, Harbin 150080, Peoples R China
[2] Heilongjiang Univ, Heilongjiang Prov Key Lab Theory & Computat Compl, Harbin 150080, Peoples R China
来源：
2021 PROCEEDINGS OF THE 40TH CHINESE CONTROL CONFERENCE (CCC) | 2021年
基金：
中国国家自然科学基金;
关键词：
Discrete-time high-order neural networks; Global exponential stability; Time-varying delays; PERIODIC-SOLUTION; INEQUALITY; CONTROLLER; EXISTENCE; SYSTEMS;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This article investigates the global exponential stability of discrete-time high-order neural networks with time-varying delays. Firstly, a novel method is proposed to establish delay-dependent sufficient conditions for global exponential stability of the zero equilibrium. The sufficient conditions include a simple matrix inequality. Then two numerical examples are given to illustrate the effectiveness of theoretical results. The proposed method has two advantages: (i) It is directly based on the definition of global exponential stability, and does not need to construct any Lyapunov-Krasovskii functional; (ii) it can result in stability criteria that are easy to verify and less conservative. More valuable, the method presented in this article is suitable for most discrete-time neural networks.
引用
收藏
页码：944 / 949
页数：6
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