Abstract

In this paper, the global exponential stability and periodicity are investigated for impulsive neural network models with Lipschitz continuous activation functions and generalized piecewise constant delay. The sufficient conditions for the existence and uniqueness of periodic solutions of the model are established by applying fixed point theorem and the successive approxima-tions method. By constructing suitable differential inequalities with general-ized piecewise constant delay, some sufficient conditions for the global expo-nential stability of the model are obtained. The methods, which does not make use of Lyapunov functional, is simple and valid for the periodicity and stabil-ity analysis of impulsive neural network models with variable and/or deviating arguments. The results extend some previous results. Typical numerical ex-amples with simulations are utilized to illustrate the validity and improvement in less conservatism of the theoretical results. This paper ends with a brief conclusion.