Exponential synchronization of inertial reaction-diffusion coupled neural networks with proportional delay via periodically intermittent control

2019 ◽  
Vol 356 ◽  
pp. 195-205 ◽  
Author(s):  
Peng Wan ◽  
Dihua Sun ◽  
Dong Chen ◽  
Min Zhao ◽  
Linjiang Zheng
Keyword(s):  
Neural Networks ◽  
Reaction Diffusion ◽  
Exponential Synchronization ◽  
Proportional Delay ◽  
Intermittent Control ◽  
Periodically Intermittent Control ◽  
Coupled Neural Networks

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

2014 ◽  
Vol 19 (1) ◽  
pp. 1-25 ◽  
Author(s):  
Qintao Gan ◽  
Hong Zhang ◽  
Jun Dong
Keyword(s):  
Neural Networks ◽  
Stochastic Analysis ◽  
Reaction Diffusion ◽  
Exponential Synchronization ◽  
Intermittent Control ◽  
Time Varying ◽  
Periodically Intermittent Control ◽  
Stochastic Disturbance ◽  
Synchronization Problem

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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