Global asymptotic stability of a class of neural networks with time varying delays


Ensari T. , Arik S., Tavsanoglu V.

IEEE International Symposium on Circuits and Systems, Vancouver, Canada, 23 - 26 May 2004, pp.820-823 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • City: Vancouver
  • Country: Canada
  • Page Numbers: pp.820-823

Abstract

This paper presents a new sufficient condition for the uniqueness and global asymptotic stability (GAS) of the equilibrium point for a larger class of neural networks with time varying delays. It is shown that the use of a more general type of Lyapunov-Krasovskii functional leads to establish global asymptotic stability of a larger class of delayed neural networks than the neural network model considered in some previous papers.