Impulsive effects on stability of Cohen-Grossberg neural networks with variable delays
Applied Mathematics and Computation
Journal of Computational and Applied Mathematics
Hi-index | 0.01 |
In this paper, an impulsive reaction-diffusion Cohen-Grossberg neural network with delays and Neumann boundary condition is considered. By utilizing Poincare inequality, constructing suitable Lyapunov functional method, some new sufficient conditions are obtained to ensure the global exponential stability of the equilibrium point. The obtained sufficient conditions depend on the reaction-diffusion terms. A comparison between our results and the previous results shows that diffusion terms can be used to exponentially stabilize some reaction-diffusion neural networks with delays and the previous results have been improved.