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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/153141
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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 Técnicas2025-09-29T09:55:00Zoai: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:34982025-09-29 09:55:00.967CONICET 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 |
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1844613661364060160 |
score |
13.070432 |