Stability analysis of inertial delayed neural network with delayed impulses via dynamic event-triggered impulsive control

Abstract

This paper investigates the stability of inertial delayed neural network under dynamic event-triggered impulsive control (DETIC). We innovate by generating the impulsive sequence through DETIC and incorporating impulsive delays, thereby enhancing the model’s practical relevance. Our methodology involves a two-step process: first, we transform the inertial neural network into a first-order differential form using appropriate vector transformations. Then, leveraging Lyapunov-based dynamic event-triggered control, we derive sufficient conditions for both uniform stability and uniform asymptotic stability of the system. To ensure practical applicability, we establish specific parameter constraints for the DETIC mechanism that precludes the Zeno phenomenon. To demonstrate the accuracy and efficacy of our theoretical results, we present two simulation examples.