Total-variation methods for gravitational-wave denoising: Performance tests on Advanced LIGO data-Reference-Cited by-同舟云学术

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Total-variation methods for gravitational-wave denoising: Performance tests on Advanced LIGO data

Published:2018-10-09 Issue:8 Volume:98 Page:
ISSN:2470-0010
Container-title:Physical Review D
language:en
Short-container-title:Phys. Rev. D

Author:

Torres-Forné Alejandro,Cuoco Elena,Marquina Antonio,Font José A.,Ibáñez José M.

Funder

Ministerio de Economía y Competitividad

Generalitat Valenciana

European Gravitational Observatory

Publisher

American Physical Society (APS)

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevD.98.084013/fulltext

Reference43 articles.

1. Characterization of the LIGO detectors during their sixth science run

2. Observation of Gravitational Waves from a Binary Black Hole Merger

3. GW151226: Observation of Gravitational Waves from a 22-Solar-Mass Binary Black Hole Coalescence

4. GW170104: Observation of a 50-Solar-Mass Binary Black Hole Coalescence at Redshift 0.2

5. GW170608: Observation of a 19 Solar-mass Binary Black Hole Coalescence

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Reconstruction of Binary Black Hole Harmonics in LIGO Using Deep Learning;The Astrophysical Journal;2024-06-26

2. Denoising gravitational-wave signals from binary black holes with a dilated convolutional autoencoder;Machine Learning: Science and Technology;2023-08-23

3. High-Accurate Robust Total Variation Denoising Algorithm With Adjustable Exponential Upper Bound Function for Micro-Thrust Measurement;IEEE Transactions on Instrumentation and Measurement;2023

4. Implementation of the regularized Rudin-Osher-Fatemi denoising method in the coherent wave burst pipeline for gravitational-wave data analysis;Physical Review D;2022-07-19

5. Detection of Non-Stationary GW Signals in High Noise From Cohen’s Class of Time–Frequency Representations Using Deep Learning;IEEE Access;2022

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