Simplex Volume Maximization (SiVM): A matrix factorization algorithm with non-negative constrains and low computing demands for the interpretation of full spectral X-ray fluorescence imaging data-Reference-Cited by-同舟云学术

Simplex Volume Maximization (SiVM): A matrix factorization algorithm with non-negative constrains and low computing demands for the interpretation of full spectral X-ray fluorescence imaging data

Published:2017-05 Issue: Volume:132 Page:179-184
ISSN:0026-265X
Container-title:Microchemical Journal
language:en
Short-container-title:Microchemical Journal

Author:

Alfeld Matthias,Wahabzada Mirwaes,Bauckhage Christian,Kersting Kristian,van der Snickt Geert,Noble Petria,Janssens Koen,Wellenreuther Gerd,Falkenberg Gerald

Funder

BMBF

Publisher

Elsevier BV

Subject

Spectroscopy,Analytical Chemistry

Reference22 articles.

1. Spectroscopic imaging: a spatial Odyssey;Adams;J. Anal. At. Spectrom.,2014

2. Strategies for processing mega-pixel X-ray fluorescence hyperspectral data: a case study on a version of Caravaggio's painting Supper at Emmaus;Alfeld;J. Anal. At. Spectrom.,2015

3. Rembrandt and/or studio, Saul and David, c. 1655: visualising the curtain using cross-section analyses and X-ray fluorescence imaging;Noble;Technè,2012

4. Rembrandt's “Saul and David” (c. 1652): use of multiple types of smalt evidenced by means of non-destructive imaging;Janssens;Microchem. J.,2016

5. Chemical imaging of stained-glass windows by means of macro X-ray fluorescence (MA-XRF) scanning;Van der Snickt;Microchem. J.,2016

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