p-th moment exponential convergence analysis for stochastic networked systems driven by fractional Brownian motion

In this paper, the existence, uniqueness and asymptotic behavior of mild solutions of stochastic neural network systems driven by fractional Brownian motion are investigated. By applying the Banach fixed point theorem, the existence and uniqueness of mild solution are analytically proved in a Hilbert space. Based on the moment inequality of wick-type integral analysis technique, the p -th moment exponential convergence condition of the mild solution is presented. Finally, two numerical examples are presented to demonstrate the validity of the theoretical results.