Exponential synchronization for stochastic neural networks with multi-delayed and Markovian switching via adaptive feedback control

被引：74

作者：

Tong, Dongbing ^{[1
]}

Zhou, Wuneng ^{[2
]}

Zhou, Xianghui ^{[2
,3
]}

Yang, Jun ^{[2
,4
]}

Zhang, Liping ^{[1
]}

Xu, Yuhua ^{[5
]}

机构：

[1] Shanghai Univ Engn Sci, Sch Elect & Elect Engn, Shanghai 201620, Peoples R China

[2] Donghua Univ, Coll Informat Sci & Technol, Shanghai 201620, Peoples R China

[3] Yangtze Univ, Freshman Educ Dept, Jing Zhou 134023, Hubei, Peoples R China

[4] Anyang Noma Univ, Sch Math & Stat, Anyang 455000, Peoples R China

[5] Ynnyang Teachers Coll, Dept Math & Finance, Shiyan 112000, Hubei, Peoples R China

来源：

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2015年 / 29卷 / 1-3期

基金：

上海市自然科学基金;

关键词：

Neural networks; Exponential synchronization; Adaptive feedback control; Multi-delayed; Stochastic noise; ASYMPTOTICAL STABILITY; JUMPING PARAMETERS; STATE ESTIMATION; TIME-DELAYS;

D O I：

10.1016/j.cnsns.2015.05.011

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper is concerned with the adaptive exponential synchronization problem for stochastic neural networks with multi-delayed and Markovian switching. A new method called M-matrix method, very different to the linear matrix inequality (LMI) method, has been proposed to solve the above problem. Meanwhile, some sufficient conditions for the exponential stability of the error system are derived. The feedback gain update laws are given by the adaptive control technique. Finally, two simulation examples are provided to demonstrate the effectiveness and applicability of the proposed design method. (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：359 / 371

页数：13

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