A nonlinear calibration transfer method based on joint kernel subspace
Shan, Peng1; Zhao, Yuhui2; Wang, Qiaoyun1; Wang, Shuyu1; Ying, Yao1; Peng, Silong3
发表期刊CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
ISSN0169-7439
2021-03-15
卷号210页码:14
通讯作者Shan, Peng(peng.shan@neuq.edu.cn)
摘要A nonlinear strategy is proposed to develop calibration transfer method with the available joint spectral data composed of the master and slave spectra of standard samples. Its core idea is to minimize the instrument-induced spectral variation in the reproducing kernel Hilbert space (RKHS) where the joint spectral data is implicitly mapped by proper kernel function. The nonlinear feature representation of master or slave spectra are reconstructed by singular value decomposition (SVD) in the RKHS. Then the transferred feature of slave spectra approaching the reconstructed feature of master spectra in the RKHS can be acquired by the procedure that (1) calculates the transfer matrix to match the maser and slave kernel features in the joint kernel subspace and (2) utilizes the transferred slave kernel feature to reconstruct the nonlinear feature representation of slave spectra. As a better feature representation suited for multivariate calibration, both the reconstructed feature of master calibration spectra and the transferred feature of slave test spectra are derived in the RKHS. A kernel partial least squares (KPLS) model built on the former is applied to the latter. The KPLS master calibration model is equivalent to a partial least squares (PLS) model built with the corresponding reconstructed master kernel feature in the joint kernel subspace. By exploiting the kernel eigenvector representations and kernel trick, a series of computationally less demanding formulas with linear operation is derived to realize the nonlinear calibration model, termed as joint kernel subspace based calibration transfer (JKSCT). JKSCT is compared with boxcar signal transfer (BST), piecewise direct standardization (PDS), multi-level simultaneous component analysis (MSCA), canonical correlation analysis based calibration transfer (CCACT), generalized least squares (GLS), slope and bias correction (SBC), spectral space transformation (SST), external parameter orthogonalization (EPO) and double competitive adaptive reweighted sampling (DCARS) on three spectral datasets. Experimental results show that JKSCT performs at least comparable with the DCARS or SST, and frequently better than the other methods.
关键词Calibration transfer Multivariate calibration Joint kernel subspace Kernel partial least squares (KPLS)
DOI10.1016/j.chemolab.2021.104247
收录类别SCI
语种英语
资助项目National Natural Science Foundation of China[61601104] ; Fundamental Research Funds for the Central Universities[N2023021]
项目资助者National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities
WOS研究方向Automation & Control Systems ; Chemistry ; Computer Science ; Instruments & Instrumentation ; Mathematics
WOS类目Automation & Control Systems ; Chemistry, Analytical ; Computer Science, Artificial Intelligence ; Instruments & Instrumentation ; Mathematics, Interdisciplinary Applications ; Statistics & Probability
WOS记录号WOS:000634801200004
出版者ELSEVIER
引用统计
被引频次:4[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/44159
专题智能制造技术与系统研究中心_多维数据分析(彭思龙)-技术团队
通讯作者Shan, Peng
作者单位1.Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Liaoning, Peoples R China
2.Northeastern Univ, Sch Comp Sci & Engn, Shenyang 110819, Liaoning, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Shan, Peng,Zhao, Yuhui,Wang, Qiaoyun,et al. A nonlinear calibration transfer method based on joint kernel subspace[J]. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS,2021,210:14.
APA Shan, Peng,Zhao, Yuhui,Wang, Qiaoyun,Wang, Shuyu,Ying, Yao,&Peng, Silong.(2021).A nonlinear calibration transfer method based on joint kernel subspace.CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS,210,14.
MLA Shan, Peng,et al."A nonlinear calibration transfer method based on joint kernel subspace".CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 210(2021):14.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Shan, Peng]的文章
[Zhao, Yuhui]的文章
[Wang, Qiaoyun]的文章
百度学术
百度学术中相似的文章
[Shan, Peng]的文章
[Zhao, Yuhui]的文章
[Wang, Qiaoyun]的文章
必应学术
必应学术中相似的文章
[Shan, Peng]的文章
[Zhao, Yuhui]的文章
[Wang, Qiaoyun]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。