A Sequential Algorithm for Signal Segmentation
AbstractThe 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 signal, 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. View Full-Text
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Hubert, P.; Padovese, L.; Stern, J.M. A Sequential Algorithm for Signal Segmentation. Entropy 2018, 20, 55.
Hubert P, Padovese L, Stern JM. A Sequential Algorithm for Signal Segmentation. Entropy. 2018; 20(1):55.Chicago/Turabian Style
Hubert, Paulo; Padovese, Linilson; Stern, Julio M. 2018. "A Sequential Algorithm for Signal Segmentation." Entropy 20, no. 1: 55.
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