期刊
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
卷 17, 期 7, 页码 3040-3049出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.cnsns.2011.11.012
关键词
Cohen-Grossberg neural networks; Synchronization; Mixed time-varying delays; Unknown parameters; Adaptive control
类别
资金
- National Natural Science Foundation of China [10671209, 11071254]
- Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry
In this paper, we investigate the synchronization problem of chaotic Cohen-Grossberg neural networks with unknown parameters and mixed time-varying delays. An adaptive linear feedback controller is designed to guarantee that the response system can be synchronized with a drive system by utilizing Lyapunov stability theory and parameter identification. Our synchronization criteria are easily verified and do not need to solve any linear matrix inequality. These results generalize a few previous known results and remove some restrictions on amplification function and time delay. This research also demonstrates the effectiveness of application in secure communication. Numerical simulations are carried out to illustrate the main results. (C) 2011 Elsevier B.V. All rights reserved.
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