• DocumentCode
    467663
  • Title

    A Synchronization Approach of Delay Chaotic Neural Networks

  • Author

    Qiao, Zong-min ; Cheng, Jia-xing ; Song, Jie

  • Volume
    1
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    334
  • Lastpage
    339
  • Abstract
    In this paper, global synchronization is discussed for chaotic neural networks time-varying delay. An effective synchronization law in matrix inequality form has been derived for time-varying delayed chaotic neural networks based on Lyapunov method and LMI technique. The advantage of the proposed approach can be performed efficiently via numerical algorithms such as the interior-point algorithms for solving LMIs. Moreover, one can get two less conservative controller gain matrixes simultaneous by solving a LMI. Numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.
  • Keywords
    Lyapunov matrix equations; chaos; delay systems; linear matrix inequalities; neurocontrollers; nonlinear control systems; synchronisation; time-varying systems; Lyapunov method; chaotic neural networks time-varying delay system; linear matrix inequality; synchronization approach; Chaos; Cybernetics; Delay effects; Linear matrix inequalities; Machine learning; Neural networks; Neurons; Numerical simulation; Signal processing algorithms; Sufficient conditions; Chaotic system; Delay; Synchronization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370165
  • Filename
    4370165