New stochastic synchronization criteria for fuzzy Markovian hybrid neural networks with random coupling strengths

被引：3
|
作者：
Zheng, Cheng-De [1 ]
Sun, Nan [1 ]
Zhang, Huaguang [2 ]
机构：
[1] Dalian Jiaotong Univ, Sch Sci, Dalian 116028, Peoples R China
[2] Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110004, Liaoning, Peoples R China
来源：
NEURAL COMPUTING & APPLICATIONS | 2019年 / 31卷 / Suppl 2期
基金：
中国国家自然科学基金;
关键词：
Barbalat's Lemma; Quadratic convex combination; Hybrid coupled neural networks; Markovian jump; Mode-dependent; Free-matrix-based integral inequalities; EXPONENTIAL SYNCHRONIZATION; STABILITY-CRITERIA; DELAY;
D O I：
10.1007/s00521-017-3043-3
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 focuses on the stochastic synchronization problem for a class of fuzzy Markovian hybrid neural networks with random coupling strengths and mode-dependent mixed time delays in the mean square. First, a novel free-matrix-based single integral inequality and two novel free-matrix-based double integral inequalities are established. Next, by employing a novel augmented Lyapunov-Krasovskii functional with several mode-dependent matrices, applying the theory of Kronecker product of matrices, Barbalat's Lemma and the new free-matrix-based integral inequalities, two delay-dependent conditions are established to achieve the globally stochastic synchronization for the mode-dependent fuzzy hybrid coupled neural networks. Finally, two numerical examples with simulation are provided to illustrate the effectiveness of the presented criteria.
引用
收藏
页码：825 / 843
页数：19
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