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A Novel Underdetermined Blind Source Separation Method and Its Application to Source Contribution Quantitative Estimation

To identify the major vibration and radiation noise, a source contribution quantitative estimation method is proposed based on underdetermined blind source separation. First, the single source points (SSPs) are identified by directly searching the identical normalized time-frequency vectors of mixed...

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Detalles Bibliográficos
Autores principales: Lu, Jiantao, Cheng, Wei, Zi, Yanyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470620/
https://www.ncbi.nlm.nih.gov/pubmed/30909420
http://dx.doi.org/10.3390/s19061413
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author Lu, Jiantao
Cheng, Wei
Zi, Yanyang
author_facet Lu, Jiantao
Cheng, Wei
Zi, Yanyang
author_sort Lu, Jiantao
collection PubMed
description To identify the major vibration and radiation noise, a source contribution quantitative estimation method is proposed based on underdetermined blind source separation. First, the single source points (SSPs) are identified by directly searching the identical normalized time-frequency vectors of mixed signals, which can improve the efficiency and accuracy in identifying SSPs. Then, the mixing matrix is obtained by hierarchical clustering, and source signals can also be recovered by the least square method. Second, the optimal combination coefficients between source signals and mixed signals can be calculated based on minimum redundant error energy. Therefore, mixed signals can be optimally linearly combined by source signals via the coefficients. Third, the energy elimination method is used to quantitatively estimate source contributions. Finally, the effectiveness of the proposed method is verified via numerical case studies and experiments with a cylindrical structure, and the results show that source signals can be effectively recovered, and source contributions can be quantitatively estimated by the proposed method.
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spelling pubmed-64706202019-04-26 A Novel Underdetermined Blind Source Separation Method and Its Application to Source Contribution Quantitative Estimation Lu, Jiantao Cheng, Wei Zi, Yanyang Sensors (Basel) Article To identify the major vibration and radiation noise, a source contribution quantitative estimation method is proposed based on underdetermined blind source separation. First, the single source points (SSPs) are identified by directly searching the identical normalized time-frequency vectors of mixed signals, which can improve the efficiency and accuracy in identifying SSPs. Then, the mixing matrix is obtained by hierarchical clustering, and source signals can also be recovered by the least square method. Second, the optimal combination coefficients between source signals and mixed signals can be calculated based on minimum redundant error energy. Therefore, mixed signals can be optimally linearly combined by source signals via the coefficients. Third, the energy elimination method is used to quantitatively estimate source contributions. Finally, the effectiveness of the proposed method is verified via numerical case studies and experiments with a cylindrical structure, and the results show that source signals can be effectively recovered, and source contributions can be quantitatively estimated by the proposed method. MDPI 2019-03-22 /pmc/articles/PMC6470620/ /pubmed/30909420 http://dx.doi.org/10.3390/s19061413 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lu, Jiantao
Cheng, Wei
Zi, Yanyang
A Novel Underdetermined Blind Source Separation Method and Its Application to Source Contribution Quantitative Estimation
title A Novel Underdetermined Blind Source Separation Method and Its Application to Source Contribution Quantitative Estimation
title_full A Novel Underdetermined Blind Source Separation Method and Its Application to Source Contribution Quantitative Estimation
title_fullStr A Novel Underdetermined Blind Source Separation Method and Its Application to Source Contribution Quantitative Estimation
title_full_unstemmed A Novel Underdetermined Blind Source Separation Method and Its Application to Source Contribution Quantitative Estimation
title_short A Novel Underdetermined Blind Source Separation Method and Its Application to Source Contribution Quantitative Estimation
title_sort novel underdetermined blind source separation method and its application to source contribution quantitative estimation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470620/
https://www.ncbi.nlm.nih.gov/pubmed/30909420
http://dx.doi.org/10.3390/s19061413
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