Synchronization of state-dependent switched neural networks via non-exponential lyapunov functions with stochastic delayed impulses.

This paper studies the synchronization of switched neural networks (SNNs) under stochastic delayed impulses (SDI), utilizing the state-dependent switching (SDS) mechanism based on the information from node dynamics. Unlike prior works, we construct a generalized non-exponential Lyapunov function for stability analysis. We extend the differential inequality with non-exponential function to the case with impulsive delay and discuss the positive effect of impulsive delay on the system's stability. By combining the Lyapunov theory, and SDS mechanisms, we derive a synchronization criterion of SNNs with SDS mechanisms under SDI. Numerical examples are presented to demonstrate the effectiveness of our results.