Refined Composite Multi-Scale Reverse Weighted Permutation Entropy and Its Applications in Ship-Radiated Noise

Ship-radiated noise is one of the important signal types under the complex ocean background, which can well reflect physical properties of ships. As one of the valid measures to characterize the complexity of ship-radiated noise, permutation entropy (PE) has the advantages of high efficiency and sim...

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Main Authors: Yuxing Li, Bo Geng, Shangbin Jiao
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/23/4/476
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author Yuxing Li
Bo Geng
Shangbin Jiao
author_facet Yuxing Li
Bo Geng
Shangbin Jiao
author_sort Yuxing Li
collection DOAJ
description Ship-radiated noise is one of the important signal types under the complex ocean background, which can well reflect physical properties of ships. As one of the valid measures to characterize the complexity of ship-radiated noise, permutation entropy (PE) has the advantages of high efficiency and simple calculation. However, PE has the problems of missing amplitude information and single scale. To address the two drawbacks, refined composite multi-scale reverse weighted PE (RCMRWPE), as a novel measurement technology of describing the signal complexity, is put forward based on refined composite multi-scale processing (RCMP) and reverse weighted PE (RWPE). RCMP is an improved method of coarse-graining, which not only solves the problem of single scale, but also improves the stability of traditional coarse-graining; RWPE has been proposed more recently, and has better inter-class separability and robustness performance to noise than PE, weighted PE (WPE), and reverse PE (RPE). Additionally, a feature extraction scheme of ship-radiated noise is proposed based on RCMRWPE, furthermore, RCMRWPE is combined with discriminant analysis classifier (DAC) to form a new classification method. After that, a large number of comparative experiments of feature extraction schemes and classification methods with two artificial random signals and six ship-radiated noise are carried out, which show that the proposed feature extraction scheme has better performance in distinguishing ability and stability than the other three similar feature extraction schemes based on multi-scale PE (MPE), multi-scale WPE (MWPE), and multi-scale RPE (MRPE), and the proposed classification method also has the highest recognition rate.
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spelling doaj.art-573940454ace489686ed40003e7120152023-11-21T16:02:09ZengMDPI AGEntropy1099-43002021-04-0123447610.3390/e23040476Refined Composite Multi-Scale Reverse Weighted Permutation Entropy and Its Applications in Ship-Radiated NoiseYuxing Li0Bo Geng1Shangbin Jiao2School of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, ChinaShip-radiated noise is one of the important signal types under the complex ocean background, which can well reflect physical properties of ships. As one of the valid measures to characterize the complexity of ship-radiated noise, permutation entropy (PE) has the advantages of high efficiency and simple calculation. However, PE has the problems of missing amplitude information and single scale. To address the two drawbacks, refined composite multi-scale reverse weighted PE (RCMRWPE), as a novel measurement technology of describing the signal complexity, is put forward based on refined composite multi-scale processing (RCMP) and reverse weighted PE (RWPE). RCMP is an improved method of coarse-graining, which not only solves the problem of single scale, but also improves the stability of traditional coarse-graining; RWPE has been proposed more recently, and has better inter-class separability and robustness performance to noise than PE, weighted PE (WPE), and reverse PE (RPE). Additionally, a feature extraction scheme of ship-radiated noise is proposed based on RCMRWPE, furthermore, RCMRWPE is combined with discriminant analysis classifier (DAC) to form a new classification method. After that, a large number of comparative experiments of feature extraction schemes and classification methods with two artificial random signals and six ship-radiated noise are carried out, which show that the proposed feature extraction scheme has better performance in distinguishing ability and stability than the other three similar feature extraction schemes based on multi-scale PE (MPE), multi-scale WPE (MWPE), and multi-scale RPE (MRPE), and the proposed classification method also has the highest recognition rate.https://www.mdpi.com/1099-4300/23/4/476multi-scale permutation entropyship-radiated noiserefined composite multi-scale reverse weighted permutation entropyfeature extraction
spellingShingle Yuxing Li
Bo Geng
Shangbin Jiao
Refined Composite Multi-Scale Reverse Weighted Permutation Entropy and Its Applications in Ship-Radiated Noise
Entropy
multi-scale permutation entropy
ship-radiated noise
refined composite multi-scale reverse weighted permutation entropy
feature extraction
title Refined Composite Multi-Scale Reverse Weighted Permutation Entropy and Its Applications in Ship-Radiated Noise
title_full Refined Composite Multi-Scale Reverse Weighted Permutation Entropy and Its Applications in Ship-Radiated Noise
title_fullStr Refined Composite Multi-Scale Reverse Weighted Permutation Entropy and Its Applications in Ship-Radiated Noise
title_full_unstemmed Refined Composite Multi-Scale Reverse Weighted Permutation Entropy and Its Applications in Ship-Radiated Noise
title_short Refined Composite Multi-Scale Reverse Weighted Permutation Entropy and Its Applications in Ship-Radiated Noise
title_sort refined composite multi scale reverse weighted permutation entropy and its applications in ship radiated noise
topic multi-scale permutation entropy
ship-radiated noise
refined composite multi-scale reverse weighted permutation entropy
feature extraction
url https://www.mdpi.com/1099-4300/23/4/476
work_keys_str_mv AT yuxingli refinedcompositemultiscalereverseweightedpermutationentropyanditsapplicationsinshipradiatednoise
AT bogeng refinedcompositemultiscalereverseweightedpermutationentropyanditsapplicationsinshipradiatednoise
AT shangbinjiao refinedcompositemultiscalereverseweightedpermutationentropyanditsapplicationsinshipradiatednoise