Stability of weighted spectral distribution in a pseudo tree-like network model  

作　　者：焦波 聂原平 黄赪东 杜静 郭荣华 黄飞 石建迈 

机构地区：[1]Luoyang Electronic Equipment Test Center,Luoyang 471003,China [2]College of Computer,National University of Defense Technology,Changsha 410073,China [3]College of Information Systems and Management,National University of Defense Technology,Changsha 410073,China

出　　处：《Chinese Physics B》2016年第5期479-486,共8页中国物理B（英文版）

基　　金：Project supported by the National Natural Science Foundation of China(Grant Nos.61402485,61303061,and 71201169)

摘　　要：The comparison of networks with different orders strongly depends on the stability analysis of graph features in evolving systems. In this paper, we rigorously investigate the stability of the weighted spectral distribution（i.e., a spectral graph feature） as the network order increases. First, we use deterministic scale-free networks generated by a pseudo treelike model to derive the precise formula of the spectral feature, and then analyze the stability of the spectral feature based on the precise formula. Except for the scale-free feature, the pseudo tree-like model exhibits the hierarchical and small-world structures of complex networks. The stability analysis is useful for the classification of networks with different orders and the similarity analysis of networks that may belong to the same evolving system.The comparison of networks with different orders strongly depends on the stability analysis of graph features in evolving systems. In this paper, we rigorously investigate the stability of the weighted spectral distribution（i.e., a spectral graph feature） as the network order increases. First, we use deterministic scale-free networks generated by a pseudo treelike model to derive the precise formula of the spectral feature, and then analyze the stability of the spectral feature based on the precise formula. Except for the scale-free feature, the pseudo tree-like model exhibits the hierarchical and small-world structures of complex networks. The stability analysis is useful for the classification of networks with different orders and the similarity analysis of networks that may belong to the same evolving system.

关 键 词：weighted spectral distribution pseudo tree-like model deterministic network scale-free and small-world network 

分 类 号：O157.5[理学—数学]