Multivariate curve resolution: A review of advanced and tailored applications and challenges

被引：316
作者：
Ruckebusch, C. [1 ]
Blanchet, L. [2 ,3 ]
机构：
[1] Univ Lille Nord France, LASIR CNRS, F-59655 Villeneuve Dascq, France
[2] Radboud Univ Nijmegen, Med Ctr, Dept Biochem 286, Nijmegen Ctr Mol Life Sci, NL-6500 HB Nijmegen, Netherlands
[3] Radboud Univ Nijmegen, Inst Mol & Mat, NL-6525 AJ Nijmegen, Netherlands
来源：
ANALYTICA CHIMICA ACTA | 2013年 / 765卷
关键词：
Chemometrics; Multivariate; Curve resolution; Mixture; MCR-ALS; ALTERNATING LEAST-SQUARES; SHIFTED FACTOR-ANALYSIS; POLYCYCLIC AROMATIC-HYDROCARBONS; PRINCIPAL COMPONENT ANALYSIS; MEASUREMENT ERROR STRUCTURE; DIODE ARRAY DETECTION; LIQUID-CHROMATOGRAPHY; FEASIBLE SOLUTIONS; BAND BOUNDARIES; LOCAL RANK;
D O I：
10.1016/j.aca.2012.12.028
中图分类号：
O65 [分析化学];
学科分类号：
070302 ; 081704 ;
摘要：
Multivariate curve resolution (MCR) is a widespread methodology for the analysis of process data in many different application fields. This article intends to propose a critical review of the recently published works. Particular attention will be paid to situations requiring advanced and tailored applications of multivariate curve resolution, dealing with improvements in preprocessing methods, multi-set data arrangements, tailored constraints, issues related to non-ideal noise structure and deviation to linearity. These analytical issues are tackling the limits of applicability of MCR methods and, therefore, they can be considered as the most challenging ones. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码：28 / 36
页数：9
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