Mean square exponential stability of stochastic Cohen-Grossberg neural networks with unbounded distributed delays (Q1958769)

Summary: 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 aid of a Lyapunov function, stochastic analysis, 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 for exponential stability for Cohen-Grossberg neural networks with unbounded distributed delays.