Mean square exponential synchronization for impulsive coupled neural networks with time‐varying delays and stochastic disturbances |
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| Authors: | Ze Tang Ju H. Park Tae H. Lee Jianwen Feng |
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| Affiliation: | 1. Nonlinear Dynamics Group, Department of Electrical Engineering, Yeungnam University, Kyonsan, Republic of Korea;2. College of Mathematics and Computational Sciences, Shenzhen University, Shenzhen, People's Republic of China |
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| Abstract: | In this article, the mean square exponential synchronization of a class of impulsive coupled neural networks with time‐varying delays and stochastic disturbances is investigated. The information transmission among the systems can be directed and lagged, that is, the coupling matrices are not needed to be symmetrical and there exist interconnection delays. The dynamical behaviors of the networks can be both continuous and discrete. Specially, the time‐varying delays are taken into consideration to describe the impulsive effects of the system. The control objective is that the trajectories of the salve system by designing suitable control schemes track the trajectories of the master system with impulsive effects. Consequently, sufficient criteria for guaranteeing the mean square exponential convergence of the two systems are obtained in view of Lyapunov stability theory, comparison principle, and mathematical induction. Finally, a numerical simulation is presented to show the verification of the main results in this article. © 2015 Wiley Periodicals, Inc. Complexity 21: 190–202, 2016 |
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| Keywords: | mean square exponential synchronization neural network stochastic disturbances impulsive effects time‐varying delays |
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