Convergence dynamics of stochastic reaction-diffusion neural networks with impulses and memory

This paper deals with the problem of global stability of stochastic reaction-diffusion neural networks with impulses. The influence of diffusions, noises, delays, impulses, and Levy jumps upon the stability of the concerned system is discussed. A sufficient condition is obtained to ensure the existence, uniqueness, and exponential p-stability of the equilibrium point of the addressed stochastic reaction-diffusion neural networks with impulses by using M-matrix theory and stochastic analysis. The proposed results extend those in the earlier literature and are easier to verify.