Global exponential synchronization of two memristor-based recurrent neural networks with time delays via static or dynamic coupling

Publication Type:
Journal Article
Citation:
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2015, 45 (2), pp. 235 - 249
Issue Date:
2015-02-01
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© 2013 IEEE. This paper is concerned with the global exponential synchronization of two memristor-based recurrent neural networks (MRNNs) with time delays via static or dynamic coupling. First, four coupling rules (i.e., static state coupling, static output coupling, dynamic state coupling, and dynamic output coupling) are designed for the exponential synchronization of drive-response pair of MRNNs. Then, several global exponential synchronization criteria are derived by constructing suitable Lyapunov-Krasovskii functionals based on the Lyapunov stability theory. Compared with existing results on synchronization of MRNNs, the conditions herein are easy to be verified. Moreover, the designed dynamic state coupling and output coupling rules have good anti-interference capacity. Finally, two illustrative examples are presented to substantiate the effectiveness and characteristics of the presented theoretical results.
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