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

页码：944 / 949

页数：6

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