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

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.

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Field Value
Source ISSN: 0003-2670
Author Ruckebusch, C., Blanchet, L.
Maintainer CCSD
Last Updated May 13, 2026, 15:58 (UTC)
Created May 13, 2026, 15:58 (UTC)
Identifier hal-00796796
Language en
contributor Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 (LASIRE) ; Institut de Chimie - CNRS Chimie (INC-CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)
creator Ruckebusch, C.
date 2013-05-13T00:00:00
harvest_object_id 495a3d1e-facf-4938-82bd-4e71864304be
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2025-11-20T00:00:00
relation info:eu-repo/semantics/altIdentifier/doi/10.1016/j.aca.2012.12.028
set_spec type:ART