Global asymptotic stability for discrete-time Cohen-Grossberg neural networks with delays by combining graph theoretic approach with Homeomorphism concept

In this paper, global asymptotic stability for a class of discrete-time Cohen-Grossberg Neural Networks with finite and infinite delays is investigated. By combining graph theoretic approach with Homeomorphism concept as well as Lyapunov functional method, two new sufficient conditions ensuring the global asymptotic stability of equilibrium point for above neural networks are established. Combining graph theoretic approach with Homeomorphism concept studies the equilibrium point of neural networks is a novel approach.