Recently, some researchers investigated the topology identification for complex networks via LaSalle's invariance principle. The principle cannot be directly applied to time-varying systems since the positive limit sets are generally not invariant. In this paper, we study the topology identification problem for a class of weighted complex networks with time-varying node systems. Adaptive identification laws are proposed to estimate the coupling parameters of the networks with and without communication delays. We prove that the asymptotic identification is ensured by a persistently exciting condition. Numerical simulations are given to demonstrate the effectiveness of the proposed approach. © 2010 American Institute of Physics. ͓doi:10.1063/1.3421947͔The topology identification, as an inverse problem, is a significant issue in the study of complex networks. For example, if a major malfunction occurs in a communication network, power network, or the Internet, it is very important to quickly detect the location of the faulty line. This paper proposes a novel adaptive identification approach for the topology identification of the weighted complex dynamical networks. We show that the concept of persistent excitation plays a key role in the process of topology identification. Our result overcomes the limitation of previous methods, which rely on the use of LaSalle's invariance principle, and is applicable to networks with time-varying node systems and diverse time-varying coupling delays.