• DocumentCode
    1898163
  • Title

    Anti-Periodic Solutions for Shunting Inhibitory Cellular Neural Networks with Continuously Distributed Delays

  • Author

    Kang, Huiyan ; Si, Ligeng

  • Author_Institution
    Sch. of Math. & Phys., Changzhou Univ., Changzhou, China
  • fYear
    2010
  • fDate
    25-26 Dec. 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper is concerned with the existence and exponential stability of anti-periodic solutions for shunting inhibitory cellular neural networks (SICNNs) with continuously distributed delays arising from the description of the neur-ons´ state in delayed neural networks. Without assuming the global Lipschitz and bounded conditions of activation functions, new sufficient conditions ensuring the existence and exponential stability of anti-periodic solutions for SICNNs are established. Moreover an example is given to illustrate the feasibility of the conditions in our results.
  • Keywords
    asymptotic stability; delays; neural nets; anti-periodic solutions; continuously distributed delays; delayed neural networks; exponential stability; shunting inhibitory cellular neural networks; Cellular neural networks; Delay; Manganese; Mathematics; Physics; Stability analysis; Sufficient conditions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
  • Conference_Location
    Wuhan
  • ISSN
    2156-7379
  • Print_ISBN
    978-1-4244-7939-9
  • Electronic_ISBN
    2156-7379
  • Type

    conf

  • DOI
    10.1109/ICIECS.2010.5678221
  • Filename
    5678221