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
收藏
页码：5559 / 5588
页数：30
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