Can One Recover the Underlying Spectral Data Matrix From a Given Borgen Plot?

ABSTRACT In multivariate curve resolution (MCR), Borgen plots represent the regions of feasible pure component profiles underlying spectral mixture data. A Borgen plot can be constructed geometrically in the low‐dimensional ‐ and ‐spaces if the so‐called outer polygon (representing nonnegativity constraints) and the inner polygon (i.e., the convex hull of the data representing points) are given. This paper asks whether it is possible to construct spectral data from the data representing points spanning the polygons and thus reconstruct the data from the associated Borgen plot. A partially positive answer is given.

Authors

Institutions

Publication Details

Journal
Journal of Chemometrics
Published
2025-03-01
DOI
https://doi.org/10.1002/cem.70016
Citations
1
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
Field-Weighted Citation Impact
0.75
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Can One Recover the Underlying Spectral Data Matrix From a Given Borgen Plot?

Martina Beese, Klaus Neymeyr, Mathias Sawall, Tomass Andersons et al.
1 citations
Journal of Chemometrics
Spectroscopy and Chemometric Analyses
0.75
article

Can One Recover the Underlying Spectral Data Matrix From a Given Borgen Plot?

Martina Beese, Klaus Neymeyr, Mathias Sawall, Tomass Andersons, Hamid Abdollahi
article en
1 citations

Abstract

ABSTRACT In multivariate curve resolution (MCR), Borgen plots represent the regions of feasible pure component profiles underlying spectral mixture data. A Borgen plot can be constructed geometrically in the low‐dimensional ‐ and ‐spaces if the so‐called outer polygon (representing nonnegativity constraints) and the inner polygon (i.e., the convex hull of the data representing points) are given. This paper asks whether it is possible to construct spectral data from the data representing points spanning the polygons and thus reconstruct the data from the associated Borgen plot. A partially positive answer is given.

Journal of ChemometricsVol. 39(3)
Institute for Advanced Studies in Basic Sciences (IR), Leibniz Institute for Catalysis (DE), University of Rostock (DE)
Openalex Percentile: Top 35%
Spectroscopy and Chemometric Analyses
0.75
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Can One Recover the Underlying Spectral Data Matrix From a Given Borgen Plot? — Martina Beese, Klaus Neymeyr, et al. · Journal of Chemometrics (2025) | TGRS Research Map | TGRS