Estimation of the Domain of Attraction of Discrete-Time Impulsive Cohen-Grossberg Neural Networks Model With Impulse Input Saturation

摘要

This paper aims at estimating the domain of attraction of discrete-time impulsive neural networks with impulse input saturation by using Lyapunov function. When an equilibrium point is locally asymptotically stable, we estimate the size of its domain of attraction and then analyze the effects of impulse input saturation. Two numerical examples are presented to unfold the effectiveness of the theoretical results.