UN MÉTODO PARA ALINEAR SERIES TEMPORALES BASADO EN CARACTERÍSTICAS DE LA ENVOLVENTE COMO PUNTO DE ANCLAJE

Resumen

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.