期刊
NEURAL NETWORKS
卷 85, 期 -, 页码 157-164出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2016.10.006
关键词
Discrete-time neural networks; Markov jump coupling; Synchronization; Time-varying delay
资金
- National Natural Science Foundation of China (NSFC) [61263020, 61673078, 61573096, 61273220]
- Chongqing Science and Technology Commission [cstc2013jcyjA40057]
In this paper, synchronization in an array of discrete-time neural networks (DTNNs) with time-varying delays coupled by Markov jump topologies is considered. It is assumed that the switching information can be collected by a tracker with a certain probability and transmitted from the tracker to controller precisely. Then the controller selects suitable control gains based on the received switching information to synchronize the network. This new control scheme makes full use of received information and overcomes the shortcomings of mode-dependent and mode-independent control schemes. Moreover, the proposed control method includes both the mode-dependent and mode-independent control techniques as special cases. By using linear matrix inequality (LMI) method and designing new Lyapunov functionals, delay-dependent conditions are derived to guarantee that the DTNNs with Markov jump topologies to be asymptotically synchronized. Compared with existing results on Markov systems which are obtained by separately using mode-dependent and mode-independent methods, our result has great flexibility in practical applications. Numerical simulations are finally given to demonstrate the effectiveness of the theoretical results. (C) 2016 Elsevier Ltd. All rights reserved.
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