Stability of switched memristive neural networks with impulse and stochastic disturbance

被引：31

作者：

Li, Can ^{[1
]}

Lian, Jie ^{[1
]}

Wang, Yun ^{[1
]}

机构：

[1] Dalian Univ Technol, Fac Elect Informat & Elect Engn, Dalian 116024, Peoples R China

来源：

NEUROCOMPUTING | 2018年 / 275卷

基金：

美国国家科学基金会;

关键词：

Switched impulsive memristive neural networks; Input-to-state stability; Multiple Lyapunov functions; TIME-VARYING DELAYS; SYNCHRONIZATION; SYSTEMS; DESIGN; CONTROLLER; PASSIVITY; DISCRETE;

D O I：

10.1016/j.neucom.2017.11.031

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper is concerned with the problem of input-to-state stability (ISS) for a class of switched impulsive memristive neural networks with stochastic disturbance. Based on the multiple Lyapunov functions method and comparison principle, new stability results for such kind of systems are derived. The cases that all subsystems are unstable and both stable/unstable subsystems coexist are considered, respectively. Time-varying delays are taken into account in the stability analysis. The mean-square ISS delay-independent sufficient conditions are presented. Finally, numerical examples are given to illustrate the effectiveness of the proposed method. (c) 2017 Elsevier B.V. All rights reserved.

引用

页码：2565 / 2573

页数：9

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