Identification in general complex delayed dynamical networks

In real-world complex networks, there exists many uncertain information, including uncertain topological structure and uncertain system parameters. This paper proposes a novel approach to identify the unknown topological structure and estimate the uncertain system parameters of a general complex delayed dynamical network together. Moreover, this method can be further extended to a general complex delayed dynamical network with two different kinds of nodes. Several typical simulations are given to verify the effectiveness of the proposed approach. It should be pointed out that the current method can be used to monitor the online evolution of the network topological structures and system parameters.