Baseline correction method based on improved adaptive iteratively reweighted penalized least squares for the X-ray fluorescence spectrum

2021 ◽  
Author(s):  
Jiang Xiaoyu ◽  
Li Fusheng ◽  
Wang Qingya ◽  
Luo Jie ◽  
Hao Jun ◽  
...  
Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 2015
Author(s):  
Feng Zhang ◽  
Xiaojun Tang ◽  
Angxin Tong ◽  
Bin Wang ◽  
Jingwei Wang

Baseline drift spectra are used for quantitative and qualitative analysis, which can easily lead to inaccurate or even wrong results. Although there are several baseline correction methods based on penalized least squares, they all have one or more parameters that must be optimized by users. For this purpose, an automatic baseline correction method based on penalized least squares is proposed in this paper. The algorithm first linearly expands the ends of the spectrum signal, and a Gaussian peak is added to the expanded range. Then, the whole spectrum is corrected by the adaptive smoothness parameter penalized least squares (asPLS) method, that is, by turning the smoothing parameter λ of asPLS to obtain a different root-mean-square error (RMSE) in the extended range, the optimal λ is selected with minimal RMSE. Finally, the baseline of the original signal is well estimated by asPLS with the optimal λ. The paper concludes with the experimental results on the simulated spectra and measured infrared spectra, demonstrating that the proposed method can automatically deal with different types of baseline drift.


2019 ◽  
Vol 58 (14) ◽  
pp. 3913 ◽  
Author(s):  
Degang Xu ◽  
Song Liu ◽  
Yaoyi Cai ◽  
Chunhua Yang

2021 ◽  
Author(s):  
Qingxian Zhang ◽  
Hui Li ◽  
Hongfei Xiao ◽  
Jian Zhang ◽  
Xiaozhe Li ◽  
...  

Baseline correction is an important step in energy-dispersive X-ray fluorescence analysis. The asymmetric least squares method (AsLS), adaptive iteratively reweighted penalized least squares method (airPLS), and asymmetrically reweighted penalized least...


2018 ◽  
Vol 45 (12) ◽  
pp. 1211001 ◽  
Author(s):  
赵恒 Zhao Heng ◽  
陈娱欣 Chen Yuxin ◽  
续小丁 Xu Xiaoding ◽  
胡波 Hu Bo

2014 ◽  
Vol 490-491 ◽  
pp. 1641-1646
Author(s):  
Wei Zhang ◽  
Yu Jun Zhang ◽  
Dong Chen ◽  
Gao Fang Yin ◽  
Xiao Ya Yu ◽  
...  

In order to overcome the baseline influence during the XRF spectra analysis, baseline deviation should be corrected. The multi-scale wavelet transform was used to remove the baseline in this paper. It is benefit that 5 decomposition levels should be selected. The whole channel was divided into several intervals. The initial interval width should be set 50. Scale coefficients were corrected according to the minimum value line. Then the scale and wavelet decomposition coefficients were reconstructed. The result shows that this method can remove the baseline effectively, especially for two sections viz. 0-400 and 1380-4095 channel.


The Analyst ◽  
2010 ◽  
Vol 135 (5) ◽  
pp. 1138 ◽  
Author(s):  
Zhi-Min Zhang ◽  
Shan Chen ◽  
Yi-Zeng Liang

2020 ◽  
Vol 53 (3) ◽  
pp. 222-233 ◽  
Author(s):  
Feng Zhang ◽  
Xiaojun Tang ◽  
Angxin Tong ◽  
Bin Wang ◽  
Jingwei Wang ◽  
...  

The Analyst ◽  
2015 ◽  
Vol 140 (1) ◽  
pp. 250-257 ◽  
Author(s):  
Sung-June Baek ◽  
Aaron Park ◽  
Young-Jin Ahn ◽  
Jaebum Choo

Baseline correction methods based on penalized least squares are successfully applied to various spectral analyses.


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