A method to align time series segments based on envelope features as anchor points
This is an incremental method for researchers in time series analysis, applicable to semi-periodic signals like canary sounds, but lacks concrete performance numbers.
The authors tackled the problem of aligning and averaging time series segments with similar patterns, proposing a method based on envelope features as anchor points, and provided a simple Python implementation for the procedure.
In the time series analysis field, there is not a unique recipe for studying signal similarities. On the other hand, averaging signals of the same nature is an essential tool in the analysis of different kinds of data. Here we propose a method to align and average segments of time series with similar patterns. A simple implementation based on \textit{python} code is provided for the procedure. The analysis was inspired by the study of canary sound syllables, but it is possible to apply it in semi periodic signals of different nature and not necessarily related to sounds.