复杂动力网络的结构识别是复杂动力网络同步的一个反问题。复杂网络的结构识别无论在理论上还是在实际应用中都具有非常重要的现实意义，已经发展成为复杂网络研究中的一个新兴的前沿研究方向。 如何基于已知的动力学或功能的信息反演网络的结构是复杂网络面临的一个巨大挑战。一方面，传统的网络结构辨识存在一些根本问题和先天不足，如一些结果对于周期和混沌系统的参数识别效果比较好，而对于稳定性系统的识别效果比较差。另一方面，由于网络节点动力学具有相关性，复杂网络在同步状态下结构无法识别。 本项目将针对几类典型的复杂动力网络模型，建立复杂动力网络结构识别的基本理论、方法与算法。同时，我们将深入探讨复杂动力网络的结构识别在实际工程力学系统中的示范应用。

Structure identification of complex dynamical networks is an inverse problem of synchronization of complex dynamical networks. Structure identification of complex network has significant importance both in theory and in practice. It has become a new research direction of research in complex networks. How to identify the structure of complex networks based on the known dynamics and some relative function information is a great challenge. On the one hand, there exists some fundamental problems for the traditional network structure identification approaches. For example, some methods are valid for the parameters identification of periodic and chaotic systems, however, they fail for the system identification of stable systems. On the other hand, due to the correlation between network nodes dynamics, it is almost impossible to identify the structure of complex networks in the synchronized state. The project aims to establish the fundamental theories, methods, and algorithms for several typical mathematical models of complex dynamical networks. At the same time, we will apply the developed theories and approaches into the structure identification of mechanical systems in practical engineering.