| 光谱学与光谱分析 |
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| Application and Improvement of Partial-Least-Squares in Fourier Transform Infrared Spectroscopy |
| ZHANG Lin, ZHANG Li-ming, LI Yan*, LIU Bing-ping, WANG Xiao-fei, WANG Jun-de |
| Laboratory of Advanced Spectroscopy, Nanjing University of Science and Technology, Nanjing 210014, China |
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Abstract Partial least squares(PLS) algorithm is an effective chemometric tool. It takes the advantages of multipal linear regression (MLR) and principal component regression (PCR), which makes Fourier transform infrared spectrometry (FTIR) more powerful and useful. Accompanied with increasing use of FTIR, the algorithm is modified and corrected under different circumstances. The applications of PLS to FTIR were mentioned. Improved algorithms were presented, such as moving windows PLS(MWPLS), robust PLS (RPLS), weighted PLS(WPLS), and non-linear PLS. Data pre-processing, selection of variable, noise elimination and non-linear model of PLS were introduced.
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Received: 2004-06-06
Accepted: 2004-09-06
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Corresponding Authors:
LI Yan
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| Cite this article: |
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ZHANG Lin,ZHANG Li-ming,LI Yan, et al. Application and Improvement of Partial-Least-Squares in Fourier Transform Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2005, 25(10): 1610-1613.
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https://www.gpxygpfx.com/EN/Y2005/V25/I10/1610 |
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