Structure Identification of General Stochastic Complex Networks via Finite-Time Adaptive Synchronization

In this paper, finite-time mean-square synchronization and structure identification of general complex network with stochastic disturbances, which is a zero-mean real m-dimension Wiener process, is investigated. The weight configuration matrix of the network under consideration needs not to he diffusive, symmetric or irreducible and is applicable to both directed and undirected networks. Based on finite-time stochastic Lyapunov stability theory, adaptive control and Ito formulation, some novel criteria for the finite-time stochastic synchronization between drive and response complex networks were derived. Simultaneously, the structure of the drive complex network is identified. Numerical simulations are provided to show the effectiveness and feasibility of the proposed schemes.