Delay-dependent robust stochastic stability of cellular neural networks with Markovian jumping parameters

The robust stochastic stability for a class of uncertain delayed cellular neural networks (DCNNs) with discrete and distributed delays and Markovian jumping parameters is considered in this paper. By introducing some free weighting matrices and constructing a Lyapunov-Krasovskii functional and combining Leibniz-Newton formula, we get a novel robust stochastic stability criteria for DCNNs with Markovian jumping parameters. Delay-dependent criteria are proposed to guarantee the robust stochastic stability of DCNNs via LMI approach. Finally, numerical examples are given to illustrate the effectiveness of the proposed method and an improvement on some existing results in the literature.