| Journal: | Anales AFA |
| Database: | |
| System number: | 000544929 |
| ISSN: | 1850-1168 |
| Authors: | Jarne, C.1 Alcain, P. N.3 |
| Institutions: | 1Universidad Nacional de Quilmes, Departamento de Ciencia y Tecnología, 2CONICET, 3Universidad Nacional de Buenos Aires, Departamento de Física FCEN, |
| Year: | 2019 |
| Season: | Dic |
| Volumen: | 30 |
| Number: | 3 |
| Pages: | 68-71 |
| Country: | Argentina |
| Language: | Español |
| English abstract | 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 |
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