Exponential stability of interval Cohen-Grossberg neural networks with inverse Lipschitz activation and mixed delays

Abstract

The exponential convergence of interval Cohen-Grossberg neural network is studied in this paper. The neural network considered in this paper has the inverse-Lipschitz continuous activation and mixed delays. Based on homomorphic method and Lyapunov stability theorem, the existence, uniqueness and exponential stability of the equilibrium point of the interval Cohen-Grossberg neural network are derived. Some comparisons and numerical examples are introduced to show the improvement of the conclusions in this paper.