%0 Journal Article
%T The study of network motifs induced from discrete time series<br>离散时间序列的网络模体分析
%A Dong Zhao
%A Li Xiang
%A <br>董昭
%A 李翔
%J 物理学报
%D 2010
%I 
%X Complex network theory is used to characterize the temporal and phase space features of a time series when it is transferred into a network. In this paper, we study the motif ranks of complex networks induced from different cat egories of time series with periodic bifurcations and chaos, which are generated with two algorithms: the Visiblity Graph (VG) algorithm and the Phase-space Reconstruction (PR) algorithm. The advantages of both algorithms are analyzed.
%K time series
%K network motif
%K chaos
%K periodic bifurcation<br>时间序列，
%K 网络模体，
%K 混沌，
%K 倍周期分岔
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=29DF2CB55EF687E7EFA80DFD4B978260&aid=CEFD41C88712C092C4364C7108AD6180&yid=140ECF96957D60B2&vid=6AC2A205FBB0EF23&iid=38B194292C032A66&sid=22E618DED444E3B5&eid=BF7851EF606736C9&journal_id=1000-3290&journal_name=物理学报&referenced_num=0&reference_num=17