Time series anomaly detection for gravitational-wave detectors based on the Hilbert–Huang transform

Time series anomaly detection for gravitational-wave detectors based on the Hilbert–Huang transform
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基于希尔伯特-黄变换的引力波探测器时间序列异常检测

DOI:
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发表时间:
2021
影响因子:
0.6
通讯作者:
S. Oh
S. Oh
中科院分区:
物理与天体物理4区
文献类型:
--
作者:
E. Son;Whansun Kim;Young;J. McIver;J. Oh;S. Oh

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We present a new event trigger generator based on the Hilbert–Huang transform, named EtaGen (η\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\eta$$\end{document}Gen). It decomposes time-series data into several adaptive modes without imposing a priori bases on the data. The adaptive modes are used to find transients (excesses) in the background noises. A clustering algorithm is used to gather excesses corresponding to a single event and to reconstruct its waveform. The performance of EtaGen is evaluated by how many injections are found in the LIGO simulated data. EtaGen is viable as an event trigger generator when compared directly with the performance of Omicron, which is currently the best event trigger generator used in the LIGO Scientific Collaboration and Virgo Collaboration.
We present a new event trigger generator based on the Hilbert–Huang transform, named EtaGen (η\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\eta$$\end{document}Gen). It decomposes time-series data into several adaptive modes without imposing a priori bases on the data. The adaptive modes are used to find transients (excesses) in the background noises. A clustering algorithm is used to gather excesses corresponding to a single event and to reconstruct its waveform. The performance of EtaGen is evaluated by how many injections are found in the LIGO simulated data. EtaGen is viable as an event trigger generator when compared directly with the performance of Omicron, which is currently the best event trigger generator used in the LIGO Scientific Collaboration and Virgo Collaboration.