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Multi-scale ensemble dispersion Lempel-Ziv complexity and its application on feature extraction for ship-radiated noise
•A new complexity index called multi-scale ensemble dispersion Lempel-Ziv complexity (MEDLZC) is proposed.•The MEDLZC is applied in feature extraction of ship-radiated noise (SN).•The proposed method has superiority in feature extraction for SN. Dispersion Lempel-Ziv complexity (DLZC) is an effectiv...
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Published in: | Applied acoustics 2024-03, Vol.218, p.109890, Article 109890 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •A new complexity index called multi-scale ensemble dispersion Lempel-Ziv complexity (MEDLZC) is proposed.•The MEDLZC is applied in feature extraction of ship-radiated noise (SN).•The proposed method has superiority in feature extraction for SN.
Dispersion Lempel-Ziv complexity (DLZC) is an effective metric of time series complexity and is widely used in the underwater acoustic field. However, DLZC is not sufficiently applicable and reflects only single scale complexity information. However, DLZC is not sufficiently applicable and reflects complex information at only a single scale. In order to solve these problems, we introduce multiple effective mapping methods into DLZC, proposing ensemble DLZC (EDLZC), which improves the applicability and stability of DLZC. Moreover, by applying coarse granulation to the EDLZC, this study proposed a novel complexity metric, termed multi-scale EDLZC (MEDLZC), which can reflect the complexity information at different scales. The results of three simulation experiments show that MEDLZC has better anti-noise performance, more sensitivity to dynamic changes and stability. In addition, the real signal experimental results indicate that proposed MEDLZC offers the best feature extraction effect for different kinds of measured SN, and average recognition rate (ARR) reaches 96.67% when the feature number is three. |
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ISSN: | 0003-682X 1872-910X |
DOI: | 10.1016/j.apacoust.2024.109890 |