Exponential synchronization for reaction-diffusion neural networks with mixed time-varying delays via periodically intermittent control
Articles
Qintao Gan
Shijiazhuang Mechanical Engineering College, China
Hong Zhang
Hebei University of Science and Technology, China
Jun Dong
State Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System, China
Published 2014-01-20
https://doi.org/10.15388/NA.2014.1.1
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Keywords

synchronization
neural networks
mixed time-varying delays
reaction-diffusion
periodically intermittent control

How to Cite

Gan, Q., Zhang, H. and Dong, J. (2014) “Exponential synchronization for reaction-diffusion neural networks with mixed time-varying delays via periodically intermittent control”, Nonlinear Analysis: Modelling and Control, 19(1), pp. 1–25. doi:10.15388/NA.2014.1.1.

Abstract

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.

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