Next Article in Journal
Nonlinear Kinetics on Lattices Based on the Kinetic Interaction Principle
Next Article in Special Issue
Complexity Analysis of Carbon Market Using the Modified Multi-Scale Entropy
Previous Article in Journal
Energy and Entropy Measures of Fuzzy Relations for Data Analysis
Previous Article in Special Issue
Entropy Change of Biological Dynamics in Asthmatic Patients and Its Diagnostic Value in Individualized Treatment: A Systematic Review
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Entropy 2018, 20(6), 425; https://doi.org/10.3390/e20060425

Hierarchical Cosine Similarity Entropy for Feature Extraction of Ship-Radiated Noise

1
School of Marine Science and technology, Northwestern Polytechnical University, Xi’an 710072, China
2
School of Physics and Information Technology, Shaanxi Normal University, Xi’an 710119, China
*
Author to whom correspondence should be addressed.
Received: 30 April 2018 / Revised: 25 May 2018 / Accepted: 31 May 2018 / Published: 1 June 2018
View Full-Text   |   Download PDF [4251 KB, uploaded 1 June 2018]   |  

Abstract

The classification performance of passive sonar can be improved by extracting the features of ship-radiated noise. Traditional feature extraction methods neglect the nonlinear features in ship-radiated noise, such as entropy. The multiscale sample entropy (MSE) algorithm has been widely used for quantifying the entropy of a signal, but there are still some limitations. To remedy this, the hierarchical cosine similarity entropy (HCSE) is proposed in this paper. Firstly, the hierarchical decomposition is utilized to decompose a time series into some subsequences. Then, the sample entropy (SE) is modified by utilizing Shannon entropy rather than conditional entropy and employing angular distance instead of Chebyshev distance. Finally, the complexity of each subsequence is quantified by the modified SE. Simulation results show that the HCSE method overcomes some limitations in MSE. For example, undefined entropy is not likely to occur in HCSE, and it is more suitable for short time series. Compared with MSE, the experimental results illustrate that the classification accuracy of real ship-radiated noise is significantly improved from 75% to 95.63% by using HCSE. Consequently, the proposed HCSE can be applied in practical applications. View Full-Text
Keywords: hierarchical cosine similarity entropy; multiscale entropy; sample entropy; feature extraction; complexity hierarchical cosine similarity entropy; multiscale entropy; sample entropy; feature extraction; complexity
Figures

Figure 1

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).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Chen, Z.; Li, Y.; Liang, H.; Yu, J. Hierarchical Cosine Similarity Entropy for Feature Extraction of Ship-Radiated Noise. Entropy 2018, 20, 425.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top