Dynamics of neural systems with distributed delays and diffusion

The paper analyzes global exponential stability of reaction-diffusion cellular neural networks with distributed delays. Some sufficient conditions are proposed to guarantee the global exponential stability of the cellular neural networks by exploiting a delay differential inequality. The conditions are formulated as an M-matrix. Different from the method in the literature, without making use of Lyapunov functionals, the method in this paper is simple and effective for the stability analysis of neural networks with delay.