Anti-synchronization of time-delayed chaotic neural networks based on adaptive control

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24 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)3498-3509
Number of pages12
JournalInternational Journal of Theoretical Physics
Issue number12
Publication statusPublished - 2009 Dec
Externally publishedYes


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

ASJC Scopus subject areas

  • Mathematics(all)
  • Physics and Astronomy (miscellaneous)


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