Mean square synchronization of neural networks with Lévy noise via sampled-data and actuator saturating controller

Abstract

The problem of synchronization via sampled-data and saturating controller is considered for stochastic time-delay neural networks with Lévy noise and Markovian switching parameters in this paper. By using of the generalized Itô׳s formula and the Lyapunov functional method, an LMI-based sufficient condition is established to ensure the mean square synchronization of the master system and the slave system. Meanwhile, the gain of the sample data and saturating controller is determined. The sufficient condition depends on not only the switching mode and time-delay, but also the upper and the lower bound of sampling intervals. A numerical example is provided to verify the usefulness of the criterion proposed in this paper.