| Full text | |
| Author(s): |
Total Authors: 3
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| Affiliation: | [1] Univ Sao Paulo, IME, BR-05508090 Sao Paulo - Brazil
[2] Univ Sao Paulo, EP, Mech Engn Dept, BR-05508010 Sao Paulo - Brazil
Total Affiliations: 2
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| 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: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 14/50279-4 - Brasil Research Centre for Gas Innovation |
| Grantee: | Julio Romano Meneghini |
| Support Opportunities: | Research Grants - Research Centers in Engineering Program |
| FAPESP's process: | 16/02175-0 - Underwater Soundscapes in the São Paulo State Coast |
| Grantee: | Linilson Rodrigues Padovese |
| Support Opportunities: | Regular Research Grants |