Period Estimation and Denoising Families of Nonuniformly Sampled Time Series

Nonuniformly sampled time series are common in astronomy, finance, and other areas of research. Commonly, these time series belong to a family of signals recorded from the same phenomenon. Period estimation and denoising of such data relies on periodograms. In particular, the Lomb-Scargle periodogra...

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Main Author:	Seguine, William
Format:	Others
Language:	English
Published:	Digital Commons @ East Tennessee State University 2019
Subjects:	Mathematics
Online Access:	https://dc.etsu.edu/etd/3668 https://dc.etsu.edu/cgi/viewcontent.cgi?article=5135&context=etd

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spelling	ndltd-ETSU-oai-dc.etsu.edu-etd-51352020-07-15T07:09:31Z Period Estimation and Denoising Families of Nonuniformly Sampled Time Series Seguine, William Nonuniformly sampled time series are common in astronomy, finance, and other areas of research. Commonly, these time series belong to a family of signals recorded from the same phenomenon. Period estimation and denoising of such data relies on periodograms. In particular, the Lomb-Scargle periodogram and its extension, the Multiband Lomb-Scargle, are at the forefront of time series period estimation. However, these methods are not without laws. This paper explores alternatives to the Lomb-Scargle and Multiband Lomb-Scargle. In particular, this thesis uses regularized least squares and the convolution theorem to introduce a spectral consensus model of a family of nonuniformly sampled time series. 2019-12-01T08:00:00Z text application/pdf https://dc.etsu.edu/etd/3668 https://dc.etsu.edu/cgi/viewcontent.cgi?article=5135&context=etd Copyright by the authors. Electronic Theses and Dissertations eng Digital Commons @ East Tennessee State University Mathematics
collection	NDLTD
language	English
format	Others
sources	NDLTD
topic	Mathematics
spellingShingle	Mathematics Seguine, William Period Estimation and Denoising Families of Nonuniformly Sampled Time Series
description	Nonuniformly sampled time series are common in astronomy, finance, and other areas of research. Commonly, these time series belong to a family of signals recorded from the same phenomenon. Period estimation and denoising of such data relies on periodograms. In particular, the Lomb-Scargle periodogram and its extension, the Multiband Lomb-Scargle, are at the forefront of time series period estimation. However, these methods are not without laws. This paper explores alternatives to the Lomb-Scargle and Multiband Lomb-Scargle. In particular, this thesis uses regularized least squares and the convolution theorem to introduce a spectral consensus model of a family of nonuniformly sampled time series.
author	Seguine, William
author_facet	Seguine, William
author_sort	Seguine, William
title	Period Estimation and Denoising Families of Nonuniformly Sampled Time Series
title_short	Period Estimation and Denoising Families of Nonuniformly Sampled Time Series
title_full	Period Estimation and Denoising Families of Nonuniformly Sampled Time Series
title_fullStr	Period Estimation and Denoising Families of Nonuniformly Sampled Time Series
title_full_unstemmed	Period Estimation and Denoising Families of Nonuniformly Sampled Time Series
title_sort	period estimation and denoising families of nonuniformly sampled time series
publisher	Digital Commons @ East Tennessee State University
publishDate	2019
url	https://dc.etsu.edu/etd/3668 https://dc.etsu.edu/cgi/viewcontent.cgi?article=5135&context=etd
work_keys_str_mv	AT seguinewilliam periodestimationanddenoisingfamiliesofnonuniformlysampledtimeseries
_version_	1719325621325135872

Period Estimation and Denoising Families of Nonuniformly Sampled Time Series

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