Structure Identification Of Single Layer And Multi-layer Networks Based On Compressed Sensing

Multi-layer complex network structure recognition is of great significance because of its wide application in information engineering and social fields.At present,multilayer network structure identification methods need to know the specific number of layers and the number of nodes in each layer in advance,but these information is often unknown in reality.Firstly,this paper introduces the basic theory of complex networks,compressed sensing theory and the existing single-layer network structure identification methods based on compressed sensing,and puts forward two methods of multi-layer network structure identification and layering based on compressed sensing.Our theoretical analysis points out that whether for ordinary multi-layer static networks or multi-layer time-varying networks,the dynamic function of each node in the network,the coupling weight between any nodes and the inner coupling matrices can be obtained through compressed sensing,and then the network is layered by the difference of node dynamic function or inner coupling matrices.Finally,the numerical experiment results show that the proposed method can achieve good results in the multi-layer network structure identification and layering.