Mode-dependent stochastic synchronization criteria for Markovian hybrid neural networks with random coupling strengths

被引：3

作者：

Zheng, Cheng-De ^{[1
]}

Sun, Nan ^{[1
]}

机构：

[1] Dalian Jiaotong Univ, Sch Sci, Dalian 116028, Peoples R China

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2017年 / 354卷 / 13期

基金：

中国国家自然科学基金;

关键词：

TIME-VARYING DELAY; UNKNOWN TRANSITION-PROBABILITIES; STABILITY ANALYSIS; EXPONENTIAL STABILITY; COMPLEX NETWORKS; SYSTEMS; STABILIZATION; DISCRETE; ARRAY;

D O I：

10.1016/j.jfranklin.2017.06.019

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 paper is concerned with the stochastic synchronization problem for a class of Markovian hybrid neural networks with random coupling strengths and mode-dependent mixed time-delays in the mean square. First, a novel inequality is established which is a double integral form of the Wirtinger-based integral inequality. Next, by employing a novel augmented Lyapunov-Krasovskii functional (LKF) with several mode-dependent matrices, applying the theory of Kronecker product of matrices, Barbalat's Lemma and the auxiliary function-based integral inequalities, several novel delay-dependent conditions are established to achieve the globally stochastic synchronization for the mode-dependent Markovian hybrid coupled neural networks. Finally, a numerical example with simulation is provided to illustrate the effectiveness of the presented criteria. (C) 2017 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

引用

页码：5559 / 5588

页数：30

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