Stability analysis for a class of delayed reaction diffusion complex networks driven by space-time white noise

This paper is concerned with the problem of almost sure exponential stability and moment exponential stability for a class of stochastic parabolic complex neural networks driven by space-time white noise. The sufficient conditions ensuring the almost sure exponential stability and moment exponential stability of the systems are developed by using strong Itô function and Nonnegative semi-martingale convergence theorem. The proposed conditions are diffusion-dependent due to the use of the new integral inequality, which is clearly more accurate than the Poincare-type inequality in previously reported literatures. In order to illustrate this more specifically, an example is provided.