Synchronization of a Class of Delayed Chaotic Neural Networks with Fully Unknown Parameters
نویسندگان
چکیده
This paper presents a global asymptotic synchronization scheme for a class of delayed chaotic neural networks when the parameters of the drive system are fully unknown and different from those of the response system. Using the Lyapunov stability theory and the inverse optimal control approach, an adaptive synchronization controller is proposed to guarantee the global asymptotic synchronization of state trajectories for two delayed chaotic neural networks with fully unknown parameters. The present controller can easily be implemented in practice. An illustrative example is used to demonstrate the effectiveness of the present method.
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تاریخ انتشار 2005