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.
张 琳，张黎明，李 燕*，刘丙萍，王晓斐，王俊德. 偏最小二乘法在傅里叶变换红外光谱中的应用及进展[J]. 光谱学与光谱分析, 2005, 25(10): 1610-1613.
ZHANG Lin, ZHANG Li-ming, LI Yan*, LIU Bing-ping, WANG Xiao-fei, WANG Jun-de. Application and Improvement of Partial-Least-Squares in Fourier Transform Infrared Spectroscopy. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2005, 25(10): 1610-1613.
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