期刊
SCIENTIFIC REPORTS
卷 9, 期 -, 页码 -出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/s41598-019-43571-2
关键词
-
资金
- French Agence Nationale de la Recherche with the PANIC project [ANR14-CE02-0015-01]
Time series measured from real-world systems are generally noisy, complex and display statistical properties that evolve continuously over time. Here, we present a method that combines wavelet analysis and non-stationary surrogates to detect short-lived spatial coherent patterns from multivariate time-series. In contrast with standard methods, the surrogate data proposed here are realisations of a non-stationary stochastic process, preserving both the amplitude and time-frequency distributions of original data. We evaluate this framework on synthetic and real-world time series, and we show that it can provide useful insights into the time-resolved structure of spatially extended systems.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据