A Sequential Algorithm for Signal Segmentation

Paulo Hubert, Linilson Padovese, Julio Stern
2018 Entropy  
The problem of event detection in general noisy signals arises in many applications; usually, either a functional form of the event is available, or a previous annotated sample with instances of the event that can be used to train a classification algorithm. There are situations, however, where neither functional forms nor annotated samples are available; then, it is necessary to apply other strategies to separate and characterize events. In this work, we analyze 15-min samples of an acoustic
more » ... gnal, and are interested in separating sections, or segments, of the signal which are likely to contain significant events. For that, we apply a sequential algorithm with the only assumption that an event alters the energy of the signal. The algorithm is entirely based on Bayesian methods.
doi:10.3390/e20010055 pmid:33265142 fatcat:n4lys7le4ne35gdvdzlgm3tjua