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Synchronization of unknown chaotic delayed competitive neural networks with different time scales based on adaptive control and parameter identification

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Abstract

In this paper, we investigate the synchronization problems of delayed competitive neural networks with different time scales and unknown parameters. A simple and robust adaptive controller is designed such that the response system can be synchronized with a drive system with unknown parameters by utilizing Lyapunov stability theory and parameter identification. Our synchronization criteria are easily verified and do not need to solve any linear matrix inequality. This research also demonstrates the effectiveness of application in secure communication. Numerical simulations are carried out to illustrate the main results.

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Authors and Affiliations

  1. Department of Basic Science, Shijiazhuang Mechanical Engineering College, Shijiazhuang, 050003, P.R. China

    Qintao Gan, Rui Xu & Xibing Kang

Authors
  1. Qintao Gan
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  2. Rui Xu
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  3. Xibing Kang
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Corresponding author

Correspondence to Qintao Gan.

Additional information

This work was supported by the National Natural Science Foundation of China (No. 10671209, No. 11071254) and the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry.

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Gan, Q., Xu, R. & Kang, X. Synchronization of unknown chaotic delayed competitive neural networks with different time scales based on adaptive control and parameter identification. Nonlinear Dyn 67, 1893–1902 (2012). https://doi.org/10.1007/s11071-011-0116-1

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  • DOI: https://doi.org/10.1007/s11071-011-0116-1

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