Stability of inertial delayed neural networks with impulsive effect
Jiangtao Qi, Wei Zhang · 2017
In this paper, we investigate the stability problem of a class of inertial delayed neural networks with impulsive effects. We consider the case when both the system state and its first derivation are subjected to the destabilizing impulses, and exploit the stabilization property of destabilizing impulses which can be used to make up for the state divergence caused by unstable inertial delayed neural networks. Based on a new time-dependent Lyapunov function and the comparison principle, some sufficient conditions guaranteeing the exponential stability of the systems are derived.