robust calibration modeling strategy for analysis of interference-subject spectral data

Preprocessing and correction of mixture spectra have been an important issue with regard to the removal of undesired systematic variation due to variations in environmental, instrumental, or sample conditions. In this article, a new robust calibration modeling strategy is proposed on the basis of in...

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Vydáno v:AIChE journal Ročník 56; číslo 1; s. 196 - 206
Hlavní autoři: Zhao, Chunhui, Gao, Furong, Yao, Yuan, Wang, Fuli
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hoboken Wiley Subscription Services, Inc., A Wiley Company 2010
Wiley
American Institute of Chemical Engineers
Témata:
Applied sciences
Calibration
Chemical engineering
Exact sciences and technology
Focusing
independent component analysis (ICA)
interference-subject spectra
Mathematical models
Preprocessing
preprocessing and correction
quality prediction
robust multivariate calibration
Spectra
Spectrum analysis
Statistical inference
Statistics
Strategy
Subspaces
preprocessing and correction
independent component analysis (ICA)
Independent component analysis
Prediction
quality prediction
Calibration
robust multivariate calibration
Modeling
interference-subject spectra
ISSN:0001-1541, 1547-5905
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Popis
Shrnutí:Preprocessing and correction of mixture spectra have been an important issue with regard to the removal of undesired systematic variation due to variations in environmental, instrumental, or sample conditions. In this article, a new robust calibration modeling strategy is proposed on the basis of independent component analysis (ICA). It aims at separating the interference-subject parasitic subspace from the interference-immune common subspace among all considered cases. The common subspace is further divided into two orthogonal parts according to their relationship with quality: one is quality-irrelevant and the other is quality-informative, in which, only the second part is employed for quality prediction. Focusing on each subspace, it identifies distinct types of underlying source components underlying different spectra subspaces, analyzes their characteristics and roles, and accordingly models them for different applications, respectively. This approach provides a comprehensive insight into the inherent nature of interference-subject mixture spectra. Furthermore, several model statistics are defined to give quantitative indication on the effectiveness of the correction strategy. The feasibility and performance of the proposed method are illustrated with data from laboratory experiments. © 2009 American Institute of Chemical Engineers AIChE J, 2010
Bibliografie:http://dx.doi.org/10.1002/aic.11998
National Natural Science Foundation of China - No. 60774068
ArticleID:AIC11998
China National 973 program - No. 2009CB320603
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ISSN:0001-1541
1547-5905
DOI:10.1002/aic.11998