Almost sure exponential synchronization of drive-response stochastic memristive neural networks

被引:22
作者
Chen, Siya [1 ]
Feng, Jianwen [1 ]
Wang, Jingyi [1 ]
Zhao, Yi [1 ]
机构
[1] Shenzhen Univ, Coll Math & Stat, Shenzhen 518060, Peoples R China
基金
中国国家自然科学基金;
关键词
Almost sure exponential synchronization; Stochastic memristive neural networks; Feedback control; Time-varying delay; STABILITY; SYSTEMS;
D O I
10.1016/j.amc.2020.125360
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper concerns with the almost sure exponential synchronization for some general classes of drive-response stochastic memristive neural networks (SMNNs) with nonidentical nodes under state feedback controllers. The SMNNs considered may include networks which are asymmetrically nondelayed and delayed coupled simultaneously, and state-dependent or even those that are subject to exogenous stochastic perturbations representatively. The main results of this paper are a collection of generic sufficient conditions for guaranteed almost sure exponential synchronization of these SMNNs, which performs great advantages compared with mean-square synchronization. Furthermore, some practical corollaries are also obtained from the main results that may be directly applied to some smaller subclasses of these networks. In particular, a simpler and more effective way of almost surely exponentially synchronizing SMNNs without delays follows by considering them as a special case of SMNNs with delays. Some numerical simulations are given to illustrate our main theoretical findings. (C) 2020 Elsevier Inc. All rights reserved.
引用
收藏
页数:15
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