Academic Editor: Juan J. Nieto
Copyright © 2010 Chuangxia Huang et al. This is an open access article distributed under the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This paper addresses the issue of mean square
exponential stability of stochastic Cohen-Grossberg neural
networks (SCGNN), whose state variables are described by
stochastic nonlinear integrodifferential equations. With the
help of Lyapunov function, stochastic analysis technique, and
inequality techniques, some novel sufficient conditions on mean
square exponential stability for SCGNN are given. Furthermore,
we also establish some sufficient conditions for checking
exponential stability for Cohen-Grossberg neural networks with
unbounded distributed delays.