Exponential synchronization of delayed neutral-type neural networks with Levy noise under non-Lipschitz condition

被引：23

作者：

Ma, Shuo ^{[1
]}

Kang, Yanmei ^{[1
]}

机构：

[1] Xi An Jiao Tong Univ, Sch Math & Stat, Xian 710049, Shaanxi, Peoples R China

来源：

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2018年 / 57卷

基金：

中国国家自然科学基金;

关键词：

Stochastic neutral-type neural networks; Non-Lipschitz condition; Levy noise; Exponential synchronization; TIME-VARYING DELAYS; CONTINUOUSLY DISTRIBUTED DELAYS; ADAPTIVE SYNCHRONIZATION; STOCHASTIC PERTURBATION; SAMPLED-DATA; MEAN-SQUARE; STABILITY; CRITERIA; APPROXIMATIONS; PARAMETERS;

D O I：

10.1016/j.cnsns.2017.10.012

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, the exponential synchronization of stochastic neutral-type neural networks with time-varying delay and Levy noise under non-Lipschitz condition is investigated for the first time. Using the general Ito's formula and the nonnegative semi-martingale convergence theorem, we derive general sufficient conditions of two kinds of exponential synchronization for the drive system and the response system with adaptive control. Numerical examples are presented to verify the effectiveness of the proposed criteria. (C) 2017 Elsevier B.V. All rights reserved.

引用

页码：372 / 387

页数：16

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