Stochastic robust stability analysis for discrete-time neural networks with Markovian jumping parameters and time delays

The problem of stochastic robust stability analysis for uncertain discrete-time delayed neural networks with Markovian jumping parameters is investigated. Based on linear matrix inequality (LMI) methodology, a novel approach is developed. The sufficient conditions of stochastic robust stable are given in terms of linear matrix inequalities. The stable criteria represented in LMI setting are less conservative and more computationally efficient than existing results reported in other literature.