Robust exponential stabilization of uncertain discrete-time stochastic switched neural networks

摘要

This paper deals with robust exponential stabilization for a class of uncertain discrete-time stochastic switched neural networks with time-delay. In the concerned model, stochastic disturbance is described by a Brownian motion. By using the average dwell time approach, the free-weighting matrix method combining with the stochastic stability theory and the multiple Lyapunov-Krasovskii functional technique, a state feedback controller is established and the sufficient condition in terms of linear matrix inequalities (LMIs) is presented, which guarantees that the neural network is robustly exponentially stabilizable. Finally, a numerical example is given to illustrate the effectiveness of the obtained results.