Global Robust Exponential Stability for a Class of Delayed Reaction-Diffusion Neural Network

In this paper, the global exponential robust stability is investigated for a class of reaction-diffusion Cohen-Grossberg neural network with delays, this neural network contains time invariant uncertain parameters whose values are unknown but bounded in given compact sets. By employing the Lyapunov-functional method, some new sufficient conditions are obtained to ensure a global exponential robust stability of equilibrium point for reaction-diffusion Cohen-Grossberg neural network with delays. These sufficient conditions depend on reaction-diffusion terms, which is a preeminent feature that distinguishes the present research from the previous results. An example and comparison are given to show the effectiveness of the obtained results.