Stabilization of stochastic delayed networks with Markovian switching via intermittent control: an averaging technique

This paper considers the stabilization of stochastic delayed networks with Markovian switching via aperiodically intermittent control (AIC). The concepts of average control ratio and average control period are proposed to characterize the distributions of control and rest intervals of AIC. It should be noted that the averaging technique used here is more general and less restrictive than the quasi-periodicity condition and minimum control ratio condition used in previous works. Then two kinds of stabilization criteria are obtained: (1) the upper bound of time delay should be less than the average control width; (2) the upper bound of time delay has no relationship with the average control width. Finally, the results are applied to studying the stabilization of coupled stochastic neural networks with Markovian switching via AIC. Numerical simulations are provided to show the effectiveness of obtained results.