Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy
In order to accurately identify various types of ships and develop coastal defenses, a single feature extraction method based on slope entropy (SlEn) and a double feature extraction method based on SlEn combined with permutation entropy (SlEn&PE) are proposed. Firstly, SlEn is used for the featu...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/24/1/22 |
| _version_ | 1797494257050714112 |
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| author | Yuxing Li Peiyuan Gao Bingzhao Tang Yingmin Yi Jianjun Zhang |
| author_facet | Yuxing Li Peiyuan Gao Bingzhao Tang Yingmin Yi Jianjun Zhang |
| author_sort | Yuxing Li |
| collection | DOAJ |
| description | In order to accurately identify various types of ships and develop coastal defenses, a single feature extraction method based on slope entropy (SlEn) and a double feature extraction method based on SlEn combined with permutation entropy (SlEn&PE) are proposed. Firstly, SlEn is used for the feature extraction of ship-radiated noise signal (SNS) compared with permutation entropy (PE), dispersion entropy (DE), fluctuation dispersion entropy (FDE), and reverse dispersion entropy (RDE), so that the effectiveness of SlEn is verified, and SlEn has the highest recognition rate calculated by the k-Nearest Neighbor (KNN) algorithm. Secondly, SlEn is combined with PE, DE, FDE, and RDE, respectively, to extract the feature of SNS for a higher recognition rate, and SlEn&PE has the highest recognition rate after the calculation of the KNN algorithm. Lastly, the recognition rates of SlEn and SlEn&PE are compared, and the recognition rates of SlEn&PE are higher than SlEn by 4.22%. Therefore, the double feature extraction method proposed in this paper is more effective in the application of ship type recognition. |
| first_indexed | 2024-03-10T01:31:45Z |
| format | Article |
| id | doaj.art-85068c7e38494a738294a21c3115d5bf |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T01:31:45Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-85068c7e38494a738294a21c3115d5bf2023-11-23T13:40:37ZengMDPI AGEntropy1099-43002021-12-012412210.3390/e24010022Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation EntropyYuxing Li0Peiyuan Gao1Bingzhao Tang2Yingmin Yi3Jianjun Zhang4School 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, ChinaSchool of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, ChinaIn order to accurately identify various types of ships and develop coastal defenses, a single feature extraction method based on slope entropy (SlEn) and a double feature extraction method based on SlEn combined with permutation entropy (SlEn&PE) are proposed. Firstly, SlEn is used for the feature extraction of ship-radiated noise signal (SNS) compared with permutation entropy (PE), dispersion entropy (DE), fluctuation dispersion entropy (FDE), and reverse dispersion entropy (RDE), so that the effectiveness of SlEn is verified, and SlEn has the highest recognition rate calculated by the k-Nearest Neighbor (KNN) algorithm. Secondly, SlEn is combined with PE, DE, FDE, and RDE, respectively, to extract the feature of SNS for a higher recognition rate, and SlEn&PE has the highest recognition rate after the calculation of the KNN algorithm. Lastly, the recognition rates of SlEn and SlEn&PE are compared, and the recognition rates of SlEn&PE are higher than SlEn by 4.22%. Therefore, the double feature extraction method proposed in this paper is more effective in the application of ship type recognition.https://www.mdpi.com/1099-4300/24/1/22ship-radiated noise signalpermutation entropydispersion entropyfluctuation dispersion entropyreverse dispersion entropyslope entropy |
| spellingShingle | Yuxing Li Peiyuan Gao Bingzhao Tang Yingmin Yi Jianjun Zhang Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy Entropy ship-radiated noise signal permutation entropy dispersion entropy fluctuation dispersion entropy reverse dispersion entropy slope entropy |
| title | Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy |
| title_full | Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy |
| title_fullStr | Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy |
| title_full_unstemmed | Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy |
| title_short | Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy |
| title_sort | double feature extraction method of ship radiated noise signal based on slope entropy and permutation entropy |
| topic | ship-radiated noise signal permutation entropy dispersion entropy fluctuation dispersion entropy reverse dispersion entropy slope entropy |
| url | https://www.mdpi.com/1099-4300/24/1/22 |
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