Principal component analysis or kernel principal component analysis based joint spectral subspace method for calibration transfer

doi:10.1016/j.saa.2019.117653

CORC > 自动化研究所 > 中国科学院自动化研究所 > 智能制造技术与系统研究中心 > 多维数据分析团队

	Principal component analysis or kernel principal component analysis based joint spectral subspace method for calibration transfer
	Shan, Peng 3; Zhao, Yuhui 1; Wang, Qiaoyun 3; Ying, Yao 3; Peng, Silong 2
刊名	SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
	2020-02-15
卷号	227 页码:16
关键词	Calibration transfer Principal component analysis (PCA) Kernel principal component analysis (KPCA) Multivariate calibration Joint spectral subspace Partial least squares (PLS)
ISSN号	1386-1425
DOI	10.1016/j.saa.2019.117653
通讯作者	Shan, Peng(peng.shan@neuq.edu.cn)
英文摘要	To transfer a calibration model in the case where only the master and slave spectra of standardization samples are available, principal component analysis (PCA) and kernel principal component analysis (KPCA) based joint spectral space (termed as JPCA or JKPCA) methods are proposed. As a feature subspace shared by master and slave spectra, the joint spectral subspace in JPCA and JKPCA are the projection of the joint spectral matrix comprising all the spectra of standardization by utilizing PCA and KPCA, respectively. The two corresponding low-dimensional feature matrices for master and slave spectra are extracted from the joint spectral subspace, and then a transfer matrix is estimated based on the least square criterion. In JKPCA, a partial least squares (PLS) model, named the primary model, is constructed using the low-dimensional feature matrix of master calibration spectra, and the model is then used to predict the transferred low-dimensional feature matrix of slave test spectra. Different from JKPCA, JPCA firstly reconstructs master calibration spectra and transferred slave test spectra, respectively. Then the primary model built on the reconstructed version of master calibration spectra is applied to predict the reconstructed version of transferred slave test spectra. A comparative study of the two proposed methods, multiplicative scatter correction (MSC), orthogonal signal correction (OSC), piecewise direct standardization (PDS), canonical correlation analysis based calibration transfer (CCACT), generalized least squares (GLS), slope and bias correction (SBC) and spectral space transformation (SST) is conducted on two datasets. All the statistical results together exhibit that the transfer ability of JKPCA is the best. Except JKPCA, JPCA performs at least comparable with the GLS or SST, and frequently better than the other methods. (C) 2019 Elsevier B.V. All rights reserved.
资助项目	National Natural Science Foundation of China[61601104] ; Natural Science Foundation of Hebei Province[F2017501052] ; Natural Science Foundation of Hebei Province[F2019501025]
WOS关键词	NEAR-INFRARED SPECTRA ; ORTHOGONAL SIGNAL CORRECTION ; LEAST-SQUARES REGRESSION ; SCATTER CORRECTION ; MULTIVARIATE CALIBRATIONS ; STANDARDIZATION ; SPECTROSCOPY ; IMPROVEMENT ; MODEL ; EXTRACTION
WOS研究方向	Spectroscopy
语种	英语
出版者	PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号	WOS:000504050600066
资助机构	National Natural Science Foundation of China ; Natural Science Foundation of Hebei Province
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/29479]
专题	自动化研究所_智能制造技术与系统研究中心_多维数据分析团队
通讯作者	Shan, Peng
作者单位	1.Northeastern Univ, Sch Comp Sci & Engn, Shenyang 110819, Liaoning, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 3.Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Liaoning, Peoples R China
推荐引用方式 GB/T 7714	Shan, Peng,Zhao, Yuhui,Wang, Qiaoyun,et al. Principal component analysis or kernel principal component analysis based joint spectral subspace method for calibration transfer[J]. SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY,2020,227:16.
APA	Shan, Peng,Zhao, Yuhui,Wang, Qiaoyun,Ying, Yao,&Peng, Silong.(2020).Principal component analysis or kernel principal component analysis based joint spectral subspace method for calibration transfer.SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY,227,16.
MLA	Shan, Peng,et al."Principal component analysis or kernel principal component analysis based joint spectral subspace method for calibration transfer".SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 227(2020):16.