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Entropy 2018, 20(1), 55; https://doi.org/10.3390/e20010055

A Sequential Algorithm for Signal Segmentation

1
Instituto de Matemática e Estatística, University of São Paulo (IME-USP), São Paulo 05508-090, Brazil
2
Mechanical Engineering Department, Escola Politécnica—University of São Paulo (EP-USP), São Paulo 05508-010, Brazil
*
Author to whom correspondence should be addressed.
Received: 29 November 2017 / Revised: 8 January 2018 / Accepted: 9 January 2018 / Published: 12 January 2018
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Abstract

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 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
Keywords: signal detection; bayesian methods; hypothesis testing; audio segmentation signal detection; bayesian methods; hypothesis testing; audio segmentation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Hubert, P.; Padovese, L.; Stern, J.M. A Sequential Algorithm for Signal Segmentation. Entropy 2018, 20, 55.

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