Global exponential stability of Cohen-Grossberg neural networks with reaction-diffusion and dirichlet boundary conditions

Abstract

In this paper, global exponential stability of Cohen-Grossberg neural networks with reaction-diffusion and Dirichlet boundary conditions is considered by using an approach based on the delay differential inequality and the fixed-point theorem. Some sufficient conditions are obtained to guarantee that the reaction-diffusion Cohen-Grossberg neural networks are globally exponentially stable. The results presented in this paper are the improvement and extension of the existed ones in some existing works. © Springer-Verlag Berlin Heidelberg 2007.