Asymptotical Stability Criteria for Time-Delay Static Neural Networks Subject to Stochastic Perturbations

This paper is concerned with the asymptotical stability analysis for stochastic static neural networks with time-varying delay. Here, the time derivative of the time-varying delay is no longer required to be smaller than one. With the use of convex polyhedron method, by constructing appropriate Lyapunov-Krasovskii functional, several delay-dependent stability sufficient conditions are formulated in terms of linear matrix inequality(LMI). A numerical example is finally provided to show the effectiveness of the proposed approach.