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A wavelet-based Gaussian method for energy dispersive X-ray fluorescence spectrum

This paper presents a wavelet-based Gaussian method (WGM) for the peak intensity estimation of energy dispersive X-ray fluorescence (EDXRF). The relationship between the parameters of Gaussian curve and the wavelet coefficients of Gaussian peak point is firstly established based on the Mexican hat w...

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Detalles Bibliográficos
Autores principales: Liu, Pan, Deng, Xiaoyan, Tang, Xin, shen, Shijian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5454144/
https://www.ncbi.nlm.nih.gov/pubmed/28607956
http://dx.doi.org/10.1016/j.heliyon.2017.e00311
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author Liu, Pan
Deng, Xiaoyan
Tang, Xin
shen, Shijian
author_facet Liu, Pan
Deng, Xiaoyan
Tang, Xin
shen, Shijian
author_sort Liu, Pan
collection PubMed
description This paper presents a wavelet-based Gaussian method (WGM) for the peak intensity estimation of energy dispersive X-ray fluorescence (EDXRF). The relationship between the parameters of Gaussian curve and the wavelet coefficients of Gaussian peak point is firstly established based on the Mexican hat wavelet. It is found that the Gaussian parameters can be accurately calculated by any two wavelet coefficients at the peak point which has to be known. This fact leads to a local Gaussian estimation method for spectral peaks, which estimates the Gaussian parameters based on the detail wavelet coefficients of Gaussian peak point. The proposed method is tested via simulated and measured spectra from an energy X-ray spectrometer, and compared with some existing methods. The results prove that the proposed method can directly estimate the peak intensity of EDXRF free from the background information, and also effectively distinguish overlap peaks in EDXRF spectrum.
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spelling pubmed-54541442017-06-12 A wavelet-based Gaussian method for energy dispersive X-ray fluorescence spectrum Liu, Pan Deng, Xiaoyan Tang, Xin shen, Shijian Heliyon Article This paper presents a wavelet-based Gaussian method (WGM) for the peak intensity estimation of energy dispersive X-ray fluorescence (EDXRF). The relationship between the parameters of Gaussian curve and the wavelet coefficients of Gaussian peak point is firstly established based on the Mexican hat wavelet. It is found that the Gaussian parameters can be accurately calculated by any two wavelet coefficients at the peak point which has to be known. This fact leads to a local Gaussian estimation method for spectral peaks, which estimates the Gaussian parameters based on the detail wavelet coefficients of Gaussian peak point. The proposed method is tested via simulated and measured spectra from an energy X-ray spectrometer, and compared with some existing methods. The results prove that the proposed method can directly estimate the peak intensity of EDXRF free from the background information, and also effectively distinguish overlap peaks in EDXRF spectrum. Elsevier 2017-05-30 /pmc/articles/PMC5454144/ /pubmed/28607956 http://dx.doi.org/10.1016/j.heliyon.2017.e00311 Text en © 2017 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Liu, Pan
Deng, Xiaoyan
Tang, Xin
shen, Shijian
A wavelet-based Gaussian method for energy dispersive X-ray fluorescence spectrum
title A wavelet-based Gaussian method for energy dispersive X-ray fluorescence spectrum
title_full A wavelet-based Gaussian method for energy dispersive X-ray fluorescence spectrum
title_fullStr A wavelet-based Gaussian method for energy dispersive X-ray fluorescence spectrum
title_full_unstemmed A wavelet-based Gaussian method for energy dispersive X-ray fluorescence spectrum
title_short A wavelet-based Gaussian method for energy dispersive X-ray fluorescence spectrum
title_sort wavelet-based gaussian method for energy dispersive x-ray fluorescence spectrum
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5454144/
https://www.ncbi.nlm.nih.gov/pubmed/28607956
http://dx.doi.org/10.1016/j.heliyon.2017.e00311
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