| Revue: | Anales AFA |
| Base de datos: | |
| Número de sistema: | 000544929 |
| ISSN: | 1850-1168 |
| Autores: | Jarne, C.1 Alcain, P. N.3 |
| Instituciones: | 1Universidad Nacional de Quilmes, Departamento de Ciencia y Tecnología, 2CONICET, 3Universidad Nacional de Buenos Aires, Departamento de Física FCEN, |
| Año: | 2019 |
| Periodo: | Dic |
| Volumen: | 30 |
| Número: | 3 |
| Paginación: | 68-71 |
| País: | Argentina |
| Idioma: | Español |
| Resumen en inglés | In the fíeld of time series analysis, there is not a unique recipe for studying signal similarities. When having the repetition of a pattern, averaging difíerent 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 difíerent nature, not necessarily related to sounds. |
| Keyword: | Signal Alignment, Time series, Averaging, Python code, Open source I Introduction |
| Texte intégral: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
