文献类型：期刊文献

英文题名：Tetradic motif profiles of horizontal visibility graphs

作者：Xie, Wen-Jie[1,2];Han, Rui-Qi[1,3];Zhou, Wei-Xing[1,2,3]

机构：[1]East China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Dept Finance, Shanghai 200237, Peoples R China;[3]East China Univ Sci & Technol, Dept Math, Shanghai 200237, Peoples R China

年份：2019

卷号：72

起止页码：544

外文期刊名：COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION

收录：;EI(收录号：20190506452426);WOS:【SCI-EXPANDED(收录号:WOS:000461321900037)】；

基金：This work was supported by the National Natural Science Foundation of China [11505063, U1811462] and Fundamental Research Funds for the Central Universities [222201818006].

语种：英文

外文关键词：Horizontal visibility graph; Tetradic motifs; Binomial measures; Fractional gaussian noises; Heartbeat rates

摘要：Network motif analysis is a useful tool for the investigation of complex networks. We study the profiles of tetradic motifs in horizontal visibility graphs (HVGs) converted from multifractal binomial measures, fractional Gaussian noises, and heartbeat rates. The profiles of tetradic motifs contain the spatial information (visibility) and temporal information (relative magnitude) among the data points in the corresponding time series. For multifractal binomial measures, the occurrence frequencies of the tetradic motifs are determined, which converge to a constant vector (2/3, 0, 8/99, 8/33, 1/99, 0). For fractional Gaussian noises, the motif occurrence frequencies are found to depend nonlinearly on the Hurst exponent and the length of time series. These findings suggest the potential ability of tetradic motif profiles in distinguishing different types of time series. Finally, we apply the tetradic motif analysis to heartbeat rates of healthy subjects, congestive heart failure (CHF) subjects, and atrial fibrillation (AF) subjects. Different subjects can be distinguished from the occurrence frequencies of tetradic motifs. (C) 2019 Elsevier B.V. All rights reserved.