Dynamics of Cohen–Grossberg neural network with variable coefficients and time-varying delays

Abstract

This paper studies the Cohen–Grossberg neural networks with variable and time-varying delays. By applying Dini derivative and introducing many real parameters, and estimating the upper bound of solutions of the system, a series of new and useful criteria on the uniform boundedness, point dissipativeness and global exponential stability for general Cohen–Grossberg neural networks. And then, some sufficient conditions on the existence and global exponential stability of periodic solutions for periodic Cohen–Grossberg neural networks are established, either. Those results obtained in this paper extend and generalize the corresponding results existing in previous literature. These criteria are important in signal processing and the design of networks.