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.

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