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Adaptive synchronization of Cohen-Grossberg neural networks with unknown parameters and mixed time-varying delays. (English) Zbl 1243.93054
Summary: 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’s 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.
MSC:
93C40Adaptive control systems
93C15Control systems governed by ODE
92B20General theory of neural networks (mathematical biology)
References:
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