• DocumentCode
    2696347
  • Title

    Robust exponential stability for uncertain stochastic neural networks with mixed time-varying delays

  • Author

    Hua, Mingang ; Fei, Juntao

  • Author_Institution
    Coll. of Comput. & Inf., Hohai Univ., Changzhou, China
  • fYear
    2010
  • fDate
    8-10 Sept. 2010
  • Firstpage
    1188
  • Lastpage
    1192
  • Abstract
    In this paper, novel theorem and corollaries are presented regarding the robust exponential stability of uncertain neural networks with mixed time-varying delays including discrete delays and distributed delays. The stability conditions in the new results improve and generalize existing ones. Several examples are included to show the effectiveness of the result.
  • Keywords
    asymptotic stability; delays; neurocontrollers; robust control; time-varying systems; discrete delays; distributed delays; mixed time-varying delays; robust exponential stability; uncertain stochastic neural networks; Artificial neural networks; Biological neural networks; Delay; Numerical stability; Robustness; Stability criteria;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Applications (CCA), 2010 IEEE International Conference on
  • Conference_Location
    Yokohama
  • Print_ISBN
    978-1-4244-5362-7
  • Electronic_ISBN
    978-1-4244-5363-4
  • Type

    conf

  • DOI
    10.1109/CCA.2010.5611331
  • Filename
    5611331