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Brillouin Frequency Shift Extraction Based on AdaBoost Algorithm
The Brillouin Optical Time-Domain Analyzer assisted by the AdaBoost Algorithm for Brillouin frequency shift (BFS) extraction is proposed and experimentally demonstrated. The Brillouin gain spectrum classification under different BFS is realized by iteratively updating the weak classifier in the form...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104193/ https://www.ncbi.nlm.nih.gov/pubmed/35591044 http://dx.doi.org/10.3390/s22093354 |
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author | Zheng, Huan Xiao, Feng Sun, Shijie Qin, Yali |
author_facet | Zheng, Huan Xiao, Feng Sun, Shijie Qin, Yali |
author_sort | Zheng, Huan |
collection | PubMed |
description | The Brillouin Optical Time-Domain Analyzer assisted by the AdaBoost Algorithm for Brillouin frequency shift (BFS) extraction is proposed and experimentally demonstrated. The Brillouin gain spectrum classification under different BFS is realized by iteratively updating the weak classifier in the form of a decision tree, forming several base classifiers and combining them into a strong classifier. Based on the pseudo-Voigt curve training set with noise, the performance of the AdaBoost Algorithm is studied, and the influence of different signal-to-noise ratio (SNR), frequency range, and frequency step is also studied. Results show that the performance of BFS extraction decreases with the decrease in SNR, the reduction in frequency range, and the increase in frequency step. |
format | Online Article Text |
id | pubmed-9104193 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91041932022-05-14 Brillouin Frequency Shift Extraction Based on AdaBoost Algorithm Zheng, Huan Xiao, Feng Sun, Shijie Qin, Yali Sensors (Basel) Communication The Brillouin Optical Time-Domain Analyzer assisted by the AdaBoost Algorithm for Brillouin frequency shift (BFS) extraction is proposed and experimentally demonstrated. The Brillouin gain spectrum classification under different BFS is realized by iteratively updating the weak classifier in the form of a decision tree, forming several base classifiers and combining them into a strong classifier. Based on the pseudo-Voigt curve training set with noise, the performance of the AdaBoost Algorithm is studied, and the influence of different signal-to-noise ratio (SNR), frequency range, and frequency step is also studied. Results show that the performance of BFS extraction decreases with the decrease in SNR, the reduction in frequency range, and the increase in frequency step. MDPI 2022-04-27 /pmc/articles/PMC9104193/ /pubmed/35591044 http://dx.doi.org/10.3390/s22093354 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Communication Zheng, Huan Xiao, Feng Sun, Shijie Qin, Yali Brillouin Frequency Shift Extraction Based on AdaBoost Algorithm |
title | Brillouin Frequency Shift Extraction Based on AdaBoost Algorithm |
title_full | Brillouin Frequency Shift Extraction Based on AdaBoost Algorithm |
title_fullStr | Brillouin Frequency Shift Extraction Based on AdaBoost Algorithm |
title_full_unstemmed | Brillouin Frequency Shift Extraction Based on AdaBoost Algorithm |
title_short | Brillouin Frequency Shift Extraction Based on AdaBoost Algorithm |
title_sort | brillouin frequency shift extraction based on adaboost algorithm |
topic | Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104193/ https://www.ncbi.nlm.nih.gov/pubmed/35591044 http://dx.doi.org/10.3390/s22093354 |
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