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  Spectram: A MATLAB® and GNU octave toolbox for transition model guided deconvolution of dynamic spectroscopic data

Rabe, M. (2020). Spectram: A MATLAB® and GNU octave toolbox for transition model guided deconvolution of dynamic spectroscopic data. Journal of Open Research Software, 8: 13. doi:10.5334/JORS.323.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0007-6056-C Version Permalink: http://hdl.handle.net/21.11116/0000-0007-6057-B
Genre: Journal Article

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323-4243-1-PB.pdf (Supplementary material), 2MB
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 Creators:
Rabe, Martin1, Author              
Affiliations:
1Interface Spectroscopy, Interface Chemistry and Surface Engineering, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society, ou_1863358              

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 Abstract: Spectroscopic data, depending on an experimentally controllable variable, contains a wealth of information for researchers. However, complex spectra with overlapping peaks and multiple transitions complicate its straightforward interpretation and often the full contained information cannot be extracted. Here, the Spectram toolbox for MATLAB® and GNU Octave is described which was developed to analyse such data by a method based on singular value decomposition (SVD) and transition model coupled recombination. The method employs user-defined transition models, which depend on the control variable and are often known, or empirical descriptions of the transitions, which often can be guessed, to deconvolute such data. The outcome are the spectral components associated to the transitions and the model parameters. Both can be directly interpreted in terms of their physical meaning. Spectram can be applied to any desired spectroscopic technique and gives full freedom in the choice of the applied models, making it highly reusable. © 2020 Ubiquity Press.

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Language(s): eng - English
 Dates: 2020-06-09
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.5334/JORS.323
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Title: Journal of Open Research Software
Source Genre: Journal
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Publ. Info: Ubiquity Press
Pages: - Volume / Issue: 8 Sequence Number: 13 Start / End Page: - Identifier: ISSN: 20499647