Improving the Sound Source Identification Performance of Sparsity Constrained Deconvolution Beamforming Utilizing SFISTA
In this paper, an alternative sparsity constrained deconvolution beamforming utilizing the smoothing fast iterative shrinkage-thresholding algorithm (SFISTA) is proposed for sound source identification. Theoretical background and solving procedures are introduced. The influence of SFISTA regularizat...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2020/1482812 |
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| _version_ | 1832568174704328704 |
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| author | Linbang Shen Zhigang Chu Long Tan Debing Chen Fangbiao Ye |
| author_facet | Linbang Shen Zhigang Chu Long Tan Debing Chen Fangbiao Ye |
| author_sort | Linbang Shen |
| collection | DOAJ |
| description | In this paper, an alternative sparsity constrained deconvolution beamforming utilizing the smoothing fast iterative shrinkage-thresholding algorithm (SFISTA) is proposed for sound source identification. Theoretical background and solving procedures are introduced. The influence of SFISTA regularization and smoothing parameters on the sound source identification performance is analyzed, and the recommended values of the parameters are obtained for the presented cases. Compared with the sparsity constrained deconvolution approach for the mapping of acoustic sources (SC-DAMAS) and the fast iterative shrinkage-thresholding algorithm (FISTA), the proposed SFISTA with appropriate regularization and smoothing parameters has faster convergence speed, higher quantification accuracy and computational efficiency, and more insensitivity to measurement noise. |
| format | Article |
| id | doaj-art-d32890b40df34d5288bb1d377dfc6064 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-d32890b40df34d5288bb1d377dfc60642025-02-03T00:59:42ZengWileyShock and Vibration1070-96221875-92032020-01-01202010.1155/2020/14828121482812Improving the Sound Source Identification Performance of Sparsity Constrained Deconvolution Beamforming Utilizing SFISTALinbang Shen0Zhigang Chu1Long Tan2Debing Chen3Fangbiao Ye4School of Automotive Engineering, Chongqing University, Chongqing 400044, ChinaSchool of Automotive Engineering, Chongqing University, Chongqing 400044, ChinaChongqing Vehicle Test & Research Institute Co., Ltd., Chongqing 401120, ChinaChongqing Vehicle Test & Research Institute Co., Ltd., Chongqing 401120, ChinaChongqing Vehicle Test & Research Institute Co., Ltd., Chongqing 401120, ChinaIn this paper, an alternative sparsity constrained deconvolution beamforming utilizing the smoothing fast iterative shrinkage-thresholding algorithm (SFISTA) is proposed for sound source identification. Theoretical background and solving procedures are introduced. The influence of SFISTA regularization and smoothing parameters on the sound source identification performance is analyzed, and the recommended values of the parameters are obtained for the presented cases. Compared with the sparsity constrained deconvolution approach for the mapping of acoustic sources (SC-DAMAS) and the fast iterative shrinkage-thresholding algorithm (FISTA), the proposed SFISTA with appropriate regularization and smoothing parameters has faster convergence speed, higher quantification accuracy and computational efficiency, and more insensitivity to measurement noise.http://dx.doi.org/10.1155/2020/1482812 |
| spellingShingle | Linbang Shen Zhigang Chu Long Tan Debing Chen Fangbiao Ye Improving the Sound Source Identification Performance of Sparsity Constrained Deconvolution Beamforming Utilizing SFISTA Shock and Vibration |
| title | Improving the Sound Source Identification Performance of Sparsity Constrained Deconvolution Beamforming Utilizing SFISTA |
| title_full | Improving the Sound Source Identification Performance of Sparsity Constrained Deconvolution Beamforming Utilizing SFISTA |
| title_fullStr | Improving the Sound Source Identification Performance of Sparsity Constrained Deconvolution Beamforming Utilizing SFISTA |
| title_full_unstemmed | Improving the Sound Source Identification Performance of Sparsity Constrained Deconvolution Beamforming Utilizing SFISTA |
| title_short | Improving the Sound Source Identification Performance of Sparsity Constrained Deconvolution Beamforming Utilizing SFISTA |
| title_sort | improving the sound source identification performance of sparsity constrained deconvolution beamforming utilizing sfista |
| url | http://dx.doi.org/10.1155/2020/1482812 |
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