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 Poincare 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. (C) 2009 Elsevier Ltd. All rights reserved.
impulsive reaction-diffusion cohen-grossberg neural network poincare inequality global exponential stability time delay