Exponential stability criterion of the switched neural networks with time-varying delay

被引：16

作者：

Wang, Hui-Ting ^{[1
]}

Liu, Then-Tao ^{[1
]}

He, Yong ^{[1
]}

机构：

[1] China Univ Geosci, Sch Automat, 388 Lumo Rd, Wuhan 430074, Hubei, Peoples R China

来源：

NEUROCOMPUTING | 2019年 / 331卷

基金：

中国国家自然科学基金;

关键词：

Switched neural networks; Average dwell time method; Time-varying delay; Free-matrix-based integral inequality; Reciprocally convex matrix inequality; Exponential stability; LINEAR-SYSTEMS; DISCRETE; STABILIZATION; DISSIPATIVITY;

D O I：

10.1016/j.neucom.2018.11.022

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, the delay-dependent stability problem of the switched neural networks with time-varying delay is considered. By taking advantage of the average dwell time method and Lyapunov-Krasovskii functional (LKF) method, and using free-matrix-based integral inequality and the extended reciprocally convex matrix inequality, a less conservative delay-dependent exponential stability criterion in linear matrix inequalities (LMIs) is developed. Two numerical examples are given to demonstrate the benefits of the proposed criterion. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：1 / 9

页数：9

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