Globally Exponential Stability of Periodic Solutions to Impulsive Neural Networks with Time-Varying Delays

Abstract

By using Schaeffer's theorem and Lyapunov functional, sufficient conditions of the existence and globally exponential stability of positive periodic solution to an impulsive neural network with time-varying delays are established. Applications, examples, and numerical analysis are given to illustrate the effectiveness of the main results.