A Sequential Algorithm for Signal Segmentation

Author(s)

Hubert, Paulo ^[1] ; Padovese, Linilson ^[2] ; Stern, Julio Michael ^[1]

Affiliation

^[1] Univ Sao Paulo, IME, BR-05508090 Sao Paulo - Brazil

^[2] Univ Sao Paulo, EP, Mech Engn Dept, BR-05508010 Sao Paulo - Brazil

• Document type: Journal article
• Source: Entropy; v. 20, n. 1 JAN 2018.
• Web of Science Citations: 2

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. (AU)

• FAPESP's process: 16/02175-0 - Underwater Soundscapes in the São Paulo State Coast
• Grantee: Linilson Rodrigues Padovese
• Support type: Regular Research Grants
• FAPESP's process: 14/50279-4 - Brasil Research Centre for Gas Innovation
• Grantee: Julio Romano Meneghini
• Support type: Research Grants - Research Centers in Engineering Program
• FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
• Grantee: José Alberto Cuminato
• Support type: Research Grants - Research, Innovation and Dissemination Centers - RIDC