Un método para alinear series temporales basado en características de la envolvente como punto de anclaje
In the eld 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. Some times averaging is essential in the analysis of the data. Here we propose a method to...
Guardado en:
| Autores principales: | , |
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| Formato: | Artículo publishedVersion |
| Lenguaje: | Inglés |
| Publicado: |
Asociación Física Argentina
2019
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/20.500.12110/afa_v30_n03_p068 |
| Aporte de: |
| Sumario: | In the eld 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. Some times 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 |
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