Stability criteria for impulsive reaction–diffusion Cohen–Grossberg neural networks with time-varying delays

This paper studies impulsive reaction–diffusion Cohen–Grossberg neural networks with time-varying delays and Neumann boundary conditions. By employing the topological degree theory, delay differential inequality with impulses, linear matrix inequality (LMI) and Poincaré inequality, a set of sufficient conditions are derived to ensure the existence, uniqueness and global exponential stability of the equilibrium point. These global exponential stability conditions depend on the reaction–diffusion term. A comparison between our results and the previous results shows that our results establish a new set of stability criteria for reaction–diffusion neural networks and have improved the previous results.