Robustness analysis for global exponential stability of reaction diffusion neural networks in the presence of uncertainty in connection weight matrices and noise

In this paper, we analyze the robustness of global exponential stability of reaction diffusion neural networks. Given a global exponential stable reaction diffusion neural networks, the upper bounds of noise intensity and parameter uncertainty in connect weight matrices are obtained. The reaction diffusion neural networks with noise will remain to be global exponential stability when noise intensity and parameter uncertainty in connect weight matrices fall in the upper bounds. A example is provided to illustrate the theory.