Robust stability analysis for Markovian jumping stochastic neural networks with mode-dependent time-varying interval delay and multiplicative noise

This paper is concerned with the problem of robust stability for aclass of Markovian jumping stochastic neural networks (MJSNNs)subject to mode-dependent time-varying interval delay andstate-multiplicative noise. Based on the Lyapunov--Krasovskii functionaland a stochastic analysis approach, some new delay-dependentsufficient conditions are obtained in the linear matrix inequality(LMI) format such that delayed MJSNNs are globally asymptoticallystable in the mean-square sense for all admissible uncertainties. Animportant feature of the results is that the stability criteria aredependent on not only the lower bound and upper bound of delay for allmodes but also the covariance matrix consisting of the correlationcoefficient. Numerical examples are given to illustrate theeffectiveness.