A method to align segments of time series based on envelope features as anchor points

Autores
Jarne, Cecilia Gisele
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In the field of time series analysis, there is not a unique recipe for studying signal similarities. When having the repetition of a pattern, averaging different signals of the same nature could be complicated. Sometimes averaging is essential in the analysis of the data. Here we propose a method to align and average segments of time series with similar patterns. For this procedure, a simple implementation based on python code is provided. This analysis was inspired by the study of canary sound syllables, but it is possible to apply it in semi-periodic signals of different nature, not necessarily related to sounds.
Fil: Jarne, Cecilia Gisele. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
Materia
Signal Alignment
Time series
Averaging
Open source
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/153141
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/153141
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A method to align segments of time series based on envelope features as anchor pointsUn método para alinear series temporales basado en características de la envolvente como punto de anclajeJarne, Cecilia GiseleSignal AlignmentTime seriesAveragingOpen sourcehttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1In the field of time series analysis, there is not a unique recipe for studying signal similarities. When having the repetition of a pattern, averaging different signals of the same nature could be complicated. Sometimes averaging is essential in the analysis of the data. Here we propose a method to align and average segments of time series with similar patterns. For this procedure, a simple implementation based on python code is provided. This analysis was inspired by the study of canary sound syllables, but it is possible to apply it in semi-periodic signals of different nature, not necessarily related to sounds.Fil: Jarne, Cecilia Gisele. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; ArgentinaAsociación Física Argentina2019-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/153141Jarne, Cecilia Gisele; A method to align segments of time series based on envelope features as anchor points; Asociación Física Argentina; Anales AFA; 30; 3; 10-2019; 1-40327-358X1850-1168CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://anales.fisica.org.ar/journal/index.php/analesafa/article/view/2238info:eu-repo/semantics/altIdentifier/doi/10.31527/analesafa.2019.30.3.68info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:49:49Zoai:ri.conicet.gov.ar:11336/153141instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:49:49.915CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A method to align segments of time series based on envelope features as anchor points
Un método para alinear series temporales basado en características de la envolvente como punto de anclaje
title A method to align segments of time series based on envelope features as anchor points
spellingShingle A method to align segments of time series based on envelope features as anchor points
Jarne, Cecilia Gisele
Signal Alignment
Time series
Averaging
Open source
title_short A method to align segments of time series based on envelope features as anchor points
title_full A method to align segments of time series based on envelope features as anchor points
title_fullStr A method to align segments of time series based on envelope features as anchor points
title_full_unstemmed A method to align segments of time series based on envelope features as anchor points
title_sort A method to align segments of time series based on envelope features as anchor points
dc.creator.none.fl_str_mv Jarne, Cecilia Gisele
author Jarne, Cecilia Gisele
author_facet Jarne, Cecilia Gisele
author_role author
dc.subject.none.fl_str_mv Signal Alignment
Time series
Averaging
Open source
topic Signal Alignment
Time series
Averaging
Open source
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In the field of time series analysis, there is not a unique recipe for studying signal similarities. When having the repetition of a pattern, averaging different signals of the same nature could be complicated. Sometimes averaging is essential in the analysis of the data. Here we propose a method to align and average segments of time series with similar patterns. For this procedure, a simple implementation based on python code is provided. This analysis was inspired by the study of canary sound syllables, but it is possible to apply it in semi-periodic signals of different nature, not necessarily related to sounds.
Fil: Jarne, Cecilia Gisele. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina
description In the field of time series analysis, there is not a unique recipe for studying signal similarities. When having the repetition of a pattern, averaging different signals of the same nature could be complicated. Sometimes averaging is essential in the analysis of the data. Here we propose a method to align and average segments of time series with similar patterns. For this procedure, a simple implementation based on python code is provided. This analysis was inspired by the study of canary sound syllables, but it is possible to apply it in semi-periodic signals of different nature, not necessarily related to sounds.
publishDate 2019
dc.date.none.fl_str_mv 2019-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/153141
Jarne, Cecilia Gisele; A method to align segments of time series based on envelope features as anchor points; Asociación Física Argentina; Anales AFA; 30; 3; 10-2019; 1-4
0327-358X
1850-1168
CONICET Digital
CONICET
url http://hdl.handle.net/11336/153141
identifier_str_mv Jarne, Cecilia Gisele; A method to align segments of time series based on envelope features as anchor points; Asociación Física Argentina; Anales AFA; 30; 3; 10-2019; 1-4
0327-358X
1850-1168
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://anales.fisica.org.ar/journal/index.php/analesafa/article/view/2238
info:eu-repo/semantics/altIdentifier/doi/10.31527/analesafa.2019.30.3.68
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Asociación Física Argentina
publisher.none.fl_str_mv Asociación Física Argentina
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1846083021556416512
score 13.22299

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