Anti-synchronization of Time-delayed Chaotic Neural Networks Based on Adaptive Control



This paper investigates the adaptive anti-synchronization problem for time-delayed chaotic neural networks with unknown parameters. Based on Lyapunov-Krasovskii stability theory and linear matrix inequality (LMI) approach, the adaptive anti-synchronization controller is designed and an analytic expression of the controller with its adaptive laws of unknown parameters is shown. The proposed controller can be obtained by solving the LMI problem. An illustrative example is given to demonstrate the effectiveness of the proposed method.


Anti-synchronization Delayed chaotic neural networks Adaptive control Linear matrix inequality (LMI) Lyapunov-Krasovskii stability theory 


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Division of Electronic and Control EngineeringWonkwang UniversityIksanKorea

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