Validation of denoising system using non-harmonic analysis and denoising convolutional neural network for removal of Gaussian noise from gravitational waves observed by LIGO

Kato T.; Hasegawa M.; Hirobayashi S.

doi:10.1016/j.ascom.2022.100607

Validation of denoising system using non-harmonic analysis and denoising convolutional neural network for removal of Gaussian noise from gravitational waves observed by LIGO

Kato T., Hasegawa M., Hirobayashi S.

Research output: Contribution to journal › Article › peer-review

Original language	Japanese
Pages (from-to)	100607-100607
Journal	Astronomy and Computing
Volume	40
DOIs	https://doi.org/10.1016/j.ascom.2022.100607
State	Published - 2022
Externally published	Yes

Access to Document

10.1016/j.ascom.2022.100607

Cite this

@article{abfae108f1b5451184c503b420472874,

title = "Validation of denoising system using non-harmonic analysis and denoising convolutional neural network for removal of Gaussian noise from gravitational waves observed by LIGO",

author = "Kato T. and Hasegawa M. and Hirobayashi S.",

year = "2022",

doi = "10.1016/j.ascom.2022.100607",

language = "日本",

volume = "40",

pages = "100607--100607",

journal = "Astronomy and Computing",

}

TY - JOUR

T1 - Validation of denoising system using non-harmonic analysis and denoising convolutional neural network for removal of Gaussian noise from gravitational waves observed by LIGO

AU - T., Kato

AU - M., Hasegawa

AU - S., Hirobayashi

PY - 2022

Y1 - 2022

U2 - 10.1016/j.ascom.2022.100607

DO - 10.1016/j.ascom.2022.100607

M3 - 学術論文

VL - 40

SP - 100607

EP - 100607

JO - Astronomy and Computing

JF - Astronomy and Computing

ER -