Stability analysis of stochastic reaction-diffusion delayed neural networks with Levy noise

摘要

This paper studies the stability of stochastic reaction-diffusion delayed recurrent neural networks with Levy noise. Using key tools such as Ito’s formula for general semimartingales, Lyapunov method, and inequality techniques, we find conditions under which the solutions to the neuron models driven by Levy noise are exponentially stable in the mean square.