Intermittent delay stabilization of complex-valued stochastic complex network

In this paper, the stabilization issue for complex-valued stochastic Markovian switching complex network with time delay and time-varying coupling structure (CSMNDC) is investigated via intermittent delay feedback control. Different from intermittent control based on current state in previous work, a class of intermittent control on the basis of past state is designed for the first time, by combining with the advantages of aperiodically intermittent control and delay feedback control. Then, some sufficient conditions are derived to guarantee the exponential stability in mean square of CSMNDC based on Lyapunov method, graph theory as well as some techniques of inequalities. In particular, the stabilization of networks is studied on complex space directly without splitting their real and imaginary parts by using complex generalized Itô’s formula. Additionally, both delay feedback control and aperiodically intermittent control are employed to solve the stabilization issue for CSMNDC here. Whereafter, the stabilization issue of complex-valued stochastic Markovian switching Cohen-Grossberg neural network with time delay and time-varying coupling structure is researched as a practical application of our theoretical results. Ultimately, a numerical example is presented to verify the validity and effectiveness of the theoretical results.