• Title of article

    Stability analysis of almost periodic solutions for delayed neural networks without global Lipschitz activation functions Original Research Article

  • Author/Authors

    Jun Zhou، نويسنده , , Weirui Zhao، نويسنده , , Guanwei Luo and Xiaohong Lv، نويسنده , , Huaping Zhu، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2011
  • Pages
    16
  • From page
    2440
  • To page
    2455
  • Abstract
    In this paper, the existence and local exponential stability of the almost periodic solutions for recurrent neural networks with mixed delays have been investigated. By applying Dini derivative and introducing many real parameters, and estimating the upper bound of solutions of the system, a series of new and useful criteria on the existence and local exponential stability of almost periodic for general delayed neural networks without global Lipschitz activation functions have been derived. Those results obtained in this paper extend and generalize the corresponding results existing in the previous literature. Two examples and numerical simulations are given to illustrate our theory.
  • Keywords
    Local exponential stability , Almost periodic solution , Neural networks , Delays
  • Journal title
    Mathematics and Computers in Simulation
  • Serial Year
    2011
  • Journal title
    Mathematics and Computers in Simulation
  • Record number

    855168