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

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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.

论文关键词:Almost sure exponential synchronization,Stochastic memristive neural networks,Feedback control,Time-varying delay

论文评审过程:Received 26 December 2019, Revised 19 April 2020, Accepted 3 May 2020, Available online 21 May 2020, Version of Record 21 May 2020.

论文官网地址:https://doi.org/10.1016/j.amc.2020.125360