期刊
NEURAL NETWORKS
卷 93, 期 -, 页码 165-175出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2017.05.008
关键词
Complex-value memristor-based neural networks; Exponential synchronization; Time-varying delays; Impulsive control
资金
- Natural Science Foundation of China [61603325]
- Innovation Program of Shanghai Municipal Education Commission [13ZZ050]
This paper investigates master-slave exponential synchronization for a class of complex-valued memristor-based neural networks with time-varying delays via discontinuous impulsive control. Firstly, the master and slave complex-valued memristor-based neural networks with time-varying delays are translated to two real-valued memristor-based neural networks. Secondly, an impulsive control law is constructed and utilized to guarantee master-slave exponential synchronization of the neural networks. Thirdly, the master-slave synchronization problems are transformed into the stability problems of the master-slave error system. By employing linear matrix inequality (LMI) technique and constructing an appropriate Lyapunov-Krasovskii functional, some sufficient synchronization criteria are derived. Finally, a numerical simulation is provided to illustrate the effectiveness of the obtained theoretical results. (C) 2017 Elsevier Ltd. All rights reserved.
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