Exponential Stability of Complex Network Model With State Coupling Driven by Fractional Gaussian Noise
Xinyu Bai, Shaojuan Ma · Mathematical Methods in the Applied Sciences · 2025
ABSTRACT This paper investigates exponential stability of complex network model driven by fractional Gaussian noise. Firstly, based on the theory of the Hilbert‐Schmidt operator and the analytic semigroups principle, the mild solution for the proposed stochastic complex networks is given. In addition, the existence and uniqueness of the solution is proved using the contraction map theory. The sufficiency criterion for the global exponential stability condition of the p‐th moment is obtained by the stochastic analysis method. Finally, the effectiveness of the obtained results is verified by providing two types of complex network models with different dimensions, which further demonstrates that the decrease in the Hurst exponent will promote the system to be faster stability.