文献类型：期刊文献

英文题名：Triadic time series motifs

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

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

年份：2019

卷号：125

期号：1

外文期刊名：EPL

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000457282200002)】；

基金：This work was supported by National Natural Science Foundation of China (11505063, 71532009, U1811462) and Fundamental Research Funds for the Central Universities (222201818006).

语种：英文

摘要：We introduce the concept of time series motifs for time series analysis. Time series motifs consider not only the spatial information of mutual visibility but also the temporal information of relative magnitude between the data points. We study the profiles of the six triadic time series motifs. The six motif occurrence frequencies are derived for uncorrelated time series, which are approximately linear functions of the length of the time series. The corresponding motif profile thus converges to a constant vector. These analytical results have been verified by numerical simulations. For fractional Gaussian noises, numerical simulations unveil the nonlinear dependence of motif occurrence frequencies on the Hurst exponent. Applications of the time series motif analysis uncover that the motif occurrence frequency distributions are able to capture the different dynamics in the heartbeat rates of healthy subjects, congestive heart failure (CHF) subjects, and atrial fibrillation (AF) subjects and in the price fluctuations of bullish and bearish markets. Our method shows its potential power to classify different types of time series and test the time irreversibility of time series. Copyright (C) EPLA, 2019