Dynamic parameters and topological structure identification of complex networks with stochastic perturbations

Abstract

In this paper, both the dynamic parameters and topological structure identification of complex networks with stochastic perturbations are investigated. An effective adaptive control law is designed in virtue of Lyapunov stability theory, Matrix theory, and Ito formula. A novel method for simultaneously identifying dynamic parameters and topological structure of complex networks with stochastic perturbations is proposed. It is shown that the new error dynamical networks both with and without communication delay and coupling delay can achieve almost sure stability. Moreover, this approach is also effective for the stochastic complex networks with node delay and coupling delay simultaneously. Finally, two representative examples further illustrate the effectiveness and correctness of the theoretical results.