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

作     者：Wang, Hui-Ting Liu, Then-Tao He, Yong 

作者机构：China Univ Geosci Sch Automat 388 Lumo Rd Wuhan 430074 Hubei Peoples R China 

出 版 物：《NEUROCOMPUTING》 (神经计算)

年 卷 期：2019年第331卷

页      面：1-9页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China Hubei Provincial Natural Science Foundation of China [2015CFA010] 111 project [B17040] 

主　　题：Switched neural networks Average dwell time method Time-varying delay Free-matrix-based integral inequality Reciprocally convex matrix inequality Exponential stability 

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.