Periodic solutions to impulsive stochastic reaction-diffusion neural networks with delays

被引：9
|
作者：
Yao, Qi [1 ]
Wang, Linshan [1 ,2 ]
Wang, Yangfan [3 ]
机构：
[1] Ocean Univ China, Sch Math Sci, Qingdao 266100, Shandong, Peoples R China
[2] Liaocheng Univ, Sch Math Sci, Liaocheng 252000, Shandong, Peoples R China
[3] Ocean Univ China, Coll Marine Life Sci, Qingdao 266100, Shandong, Peoples R China
来源：
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2019年 / 78卷
基金：
中国国家自然科学基金;
关键词：
Stochastic reaction-diffusion neural networks with delays; Impulsive; Mild periodic solutions; Stability; TIME-VARYING DELAYS; EXPONENTIAL STABILITY; DIFFERENTIAL-EQUATIONS; EXISTENCE; SYNCHRONIZATION; UNIQUENESS;
D O I：
10.1016/j.cnsns.2019.104865
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, the aims are to study the existence and stability of mild periodic solutions to impulsive stochastic reaction-diffusion neural networks (ISRDNNs) with delays. First, key issues of the Markov property of mild solutions to ISRDNNs with delays are presented in the space of piecewise continuous functions. Next, combining the operator semigroup method with other mathematical techniques, the existence of mild periodic solutions is proposed and some relevant results are generalized. Then, the exponential stability of mild periodic solutions is discussed and some easy-to-test sufficient conditions are obtained by using the Lyapunov method. Finally, numerical simulations are provided to illustrate the effectiveness of our results. (C) 2019 Elsevier B.V. All rights reserved.
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页数：11
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