Exponential synchronization for reaction-diffusion neural networks with mixed time-varying delays via periodically intermittent control

Nonlinear Analysis

Hong Zhang¹  Qintao Gan²  Jun Dong³ 

[1] Hebei University of Science and Technology, China;Shijiazhuang Mechanical Engineering College, China;State Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System, China;

关键词: synchronization;    neural networks;    mixed time-varying delays;    reaction-diffusion;    periodically intermittent control;   

DOI  :  10.15388/NA.2014.1.1

来源: DOAJ

【 摘 要 】

This paper deals with the exponential synchronization problem for reaction-diffusion neural networks with mixed time-varying delays and stochastic disturbance. By using stochastic analysis approaches and constructing a novel Lyapunov–Krasovskii functional, a periodically intermittent controller is first proposed to guarantee the exponential synchronization of reaction-diffusion neural networks with mixed time-varying delays and stochastic disturbance in terms of p-norm. The obtained synchronization results are easy to check and improve upon the existing ones. Particularly, the traditional assumptions on control width and time-varying delays are removed in this paper. This paper also presents two illustrative examples and uses simulated results of these examples to show the feasibility and effectiveness of the proposed scheme.

【 授权许可】

Unknown