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Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic

After reviewing the standard hypothesis test and the matched filter technique to identify gravitational waves under Gaussian noises, we introduce two methods to deal with non-Gaussian stationary noises. We formulate the likelihood ratio function under weakly non-Gaussian noises through the Edgeworth...

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Autor principal: YOKOYAMA, Jun’ichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Japan Academy 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4335139/
https://www.ncbi.nlm.nih.gov/pubmed/25504231
http://dx.doi.org/10.2183/pjab.90.422
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author YOKOYAMA, Jun’ichi
author_facet YOKOYAMA, Jun’ichi
author_sort YOKOYAMA, Jun’ichi
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description After reviewing the standard hypothesis test and the matched filter technique to identify gravitational waves under Gaussian noises, we introduce two methods to deal with non-Gaussian stationary noises. We formulate the likelihood ratio function under weakly non-Gaussian noises through the Edgeworth expansion and strongly non-Gaussian noises in terms of a new method we call Gaussian mapping where the observed marginal distribution and the two-body correlation function are fully taken into account. We then apply these two approaches to Student’s t-distribution which has a larger tails than Gaussian. It is shown that while both methods work well in the case the non-Gaussianity is small, only the latter method works well for highly non-Gaussian case.
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spelling pubmed-43351392015-03-19 Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic YOKOYAMA, Jun’ichi Proc Jpn Acad Ser B Phys Biol Sci Original Article After reviewing the standard hypothesis test and the matched filter technique to identify gravitational waves under Gaussian noises, we introduce two methods to deal with non-Gaussian stationary noises. We formulate the likelihood ratio function under weakly non-Gaussian noises through the Edgeworth expansion and strongly non-Gaussian noises in terms of a new method we call Gaussian mapping where the observed marginal distribution and the two-body correlation function are fully taken into account. We then apply these two approaches to Student’s t-distribution which has a larger tails than Gaussian. It is shown that while both methods work well in the case the non-Gaussianity is small, only the latter method works well for highly non-Gaussian case. The Japan Academy 2014-12-11 /pmc/articles/PMC4335139/ /pubmed/25504231 http://dx.doi.org/10.2183/pjab.90.422 Text en © 2014 The Japan Academy This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
YOKOYAMA, Jun’ichi
Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic
title Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic
title_full Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic
title_fullStr Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic
title_full_unstemmed Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic
title_short Toward the detection of gravitational waves under non-Gaussian noises I. Locally optimal statistic
title_sort toward the detection of gravitational waves under non-gaussian noises i. locally optimal statistic
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4335139/
https://www.ncbi.nlm.nih.gov/pubmed/25504231
http://dx.doi.org/10.2183/pjab.90.422
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