Global stability analysis in Cohen-Grossberg neural networks with delays and inverse Holder neuron activation functions
In this paper, a novel class of Cohen-Grossberg neural networks with delays and inverse Holder neuron activation functions are presented. By using the topological degree theory and linear matrix inequality (LMI) technique, the existence and uniqueness of equilibrium point for such Cohen-Grossberg neural networks is investigated. By constructing appropriate Lyapunov function, a sufficient condition which ensures the global exponential stability of the equilibrium point is established. Two numerical examples are provided to demonstrate the effectiveness of the theoretical results. (C) 2010 Elsevier Inc. All rights reserved.
neural networks topological degree global exponential stability cohen-grossberg model inverse holder functions