• DocumentCode
    478116
  • Title

    Existence of Periodic Solution for High-Order Neural Networks with Neutral Delay

  • Author

    Tang, Mei-Lan ; Liu, Xin-Ge

  • Author_Institution
    Sch. of Math. Sci. & Comput. Technol., Central South Univ., Changsha
  • Volume
    2
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    360
  • Lastpage
    364
  • Abstract
    In this paper, high-order neural networks with neutral delay are considered. Based on the continuation theorem of coincidence degree theory and a priori estimate, new result on the existence of periodic solution for delayed high-order Hopfield-type neural networks with neutral delay is established. The result of this paper is new and it complements previously known results. An illustrative example is given to demonstrate the effectiveness of our result.
  • Keywords
    neural nets; high-order neural networks; neutral delay; periodic solution; Artificial neural networks; Biological neural networks; Biomedical signal processing; Chaos; Computer networks; Delay effects; Delay estimation; Hopfield neural networks; Neural networks; Stability; continuation theorem; high-order neural networks; neutral delay; periodic solution; priori estimate;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2008. ICNC '08. Fourth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-0-7695-3304-9
  • Type

    conf

  • DOI
    10.1109/ICNC.2008.7
  • Filename
    4667017
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=478116