• DocumentCode
    232048
  • Title

    Almost periodicity in a harvesting Lotka-Volterra recurrent neural networks with mixed delays and impulses

  • Author

    Yao Xiaojie ; Qin Fajin

  • Author_Institution
    Dept. of Math. & Comput. Sci., Liuzhou Teachers Coll., Liuzhou, China
  • fYear
    2014
  • fDate
    28-30 July 2014
  • Firstpage
    5107
  • Lastpage
    5112
  • Abstract
    By using the theory of exponential dichotomy and Banach fixed point theorem, this paper is concerned with the problem of the existence and uniqueness of positive almost periodic solution in a harvesting Lotka-Volterra recurrent neural networks with mixed delays and impulses. To a certain extent, our work in this paper extend and improve some result in recent years. Finally, an example is given to illustrate the feasibility and effectiveness of the main result.
  • Keywords
    Volterra equations; delays; neural nets; Banach fixed point theorem; exponential dichotomy; harvesting Lotka-Volterra recurrent neural networks; mixed delays; mixed impulses; Computer science; Delays; Educational institutions; Electronic mail; Mathematics; Recurrent neural networks; Sufficient conditions; Impulses; Lotka-Volterra Recurrent Neural Networks; Mixed Delays; Positive Almost Periodic Solution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2014 33rd Chinese
  • Conference_Location
    Nanjing
  • Type

    conf

  • DOI
    10.1109/ChiCC.2014.6895809
  • Filename
    6895809