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

被引：6

作者：

Son, Edwin J. ^{[1
]}

Kim, Whansun ^{[1
]}

Kim, Young-Min ^{[2
]}

McIver, Jessica ^{[3
]}

Oh, John J. ^{[1
]}

Oh, Sang Hoon ^{[1
]}

机构：

[1] Natl Inst Math Sci, Div Basic Res Ind Math, Daejeon 34047, South Korea

[2] Ulsan Natl Inst Sci & Technol, Dept Phys, Ulsan 44919, South Korea

[3] Univ British Columbia, Dept Phys & Astron, Vancouver, BC V6T 1Z4, Canada

来源：

JOURNAL OF THE KOREAN PHYSICAL SOCIETY | 2021年 / 78卷 / 10期

基金：

新加坡国家研究基金会; 美国国家科学基金会;

关键词：

Event trigger generator; Hilbert-Huang transform; GW data analysis; EMPIRICAL MODE DECOMPOSITION;

D O I：

10.1007/s40042-021-00094-2

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

We present a new event trigger generator based on the Hilbert-Huang transform, named EtaGen (eta 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.

引用

页码：878 / 885

页数：8

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