An active constraint approach to identify ...
Type de document :
Article dans une revue scientifique: Article original
PMID :
URL permanente :
Titre :
An active constraint approach to identify essential spectral information in noisy data
Auteur(s) :
Sawall, M. [Auteur]
Ruckebusch, Cyril [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516
Beese, M. [Auteur]
Francke, R. [Auteur]
Prudlik, A. [Auteur]
Neymeyr, K. [Auteur]
Ruckebusch, Cyril [Auteur]

Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516
Beese, M. [Auteur]
Francke, R. [Auteur]
Prudlik, A. [Auteur]
Neymeyr, K. [Auteur]
Titre de la revue :
Analytica Chimica Acta
Nom court de la revue :
Anal Chim Acta
Numéro :
1233
Pagination :
340448
Date de publication :
2022-10-27
ISSN :
1873-4324
Mot(s)-clé(s) en anglais :
Ray casting
Area of feasible solutions
Essential spectra and frequencies
Multivariate curve resolution
Area of feasible solutions
Essential spectra and frequencies
Multivariate curve resolution
Discipline(s) HAL :
Chimie/Chimie théorique et/ou physique
Résumé en anglais : [en]
Multivariate curve resolution (MCR) methods aim at extracting pure component profiles from mixed spectral data and can be applied to high-dimensional data, e.g., from process spectroscopy or hyperspectral imaging techniques. ...
Lire la suite >Multivariate curve resolution (MCR) methods aim at extracting pure component profiles from mixed spectral data and can be applied to high-dimensional data, e.g., from process spectroscopy or hyperspectral imaging techniques. One often observes that some parts of this data, namely certain rows and columns of the data matrix, are considered essential for MCR outcomes, while other parts are of minor importance. Some methods for determining essential data are known, but all have different disadvantages concerning the application for noisy data. This work presents a new approach on how to detect the essential information for noisy, experimental spectral data. Active nonnegativity constraints in combination with duality arguments are the key ingredients for determining essential spectra and frequency channels. The new approach is conceptually simple, computationally cheap and stable with respect to noise. The algorithm is tested for noisy experimental Raman, UV–Vis and FTIR-SEC data.Lire moins >
Lire la suite >Multivariate curve resolution (MCR) methods aim at extracting pure component profiles from mixed spectral data and can be applied to high-dimensional data, e.g., from process spectroscopy or hyperspectral imaging techniques. One often observes that some parts of this data, namely certain rows and columns of the data matrix, are considered essential for MCR outcomes, while other parts are of minor importance. Some methods for determining essential data are known, but all have different disadvantages concerning the application for noisy data. This work presents a new approach on how to detect the essential information for noisy, experimental spectral data. Active nonnegativity constraints in combination with duality arguments are the key ingredients for determining essential spectra and frequency channels. The new approach is conceptually simple, computationally cheap and stable with respect to noise. The algorithm is tested for noisy experimental Raman, UV–Vis and FTIR-SEC data.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
Université de Lille
CNRS
CNRS
Collections :
Date de dépôt :
2024-02-28T22:17:52Z
2024-03-19T09:32:39Z
2024-03-19T09:32:39Z