Decoding ‘Maximum Entropy’ Deconvolution

For over five decades, the mathematical procedure termed “maximum entropy” (M-E) has been used to deconvolve structure in spectra, optical and otherwise, although quantitative measures of performance remain unknown. Here, we examine this procedure analytically for the lowest two orders for a Lorentz...

Descripción completa

Detalles Bibliográficos
Autores principales: Le, Long V., Kim, Tae Jung, Kim, Young Dong, Aspnes, David E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9497885/
https://www.ncbi.nlm.nih.gov/pubmed/36141124
http://dx.doi.org/10.3390/e24091238
_version_ 1784794618241482752
author Le, Long V.
Kim, Tae Jung
Kim, Young Dong
Aspnes, David E.
author_facet Le, Long V.
Kim, Tae Jung
Kim, Young Dong
Aspnes, David E.
author_sort Le, Long V.
collection PubMed
description For over five decades, the mathematical procedure termed “maximum entropy” (M-E) has been used to deconvolve structure in spectra, optical and otherwise, although quantitative measures of performance remain unknown. Here, we examine this procedure analytically for the lowest two orders for a Lorentzian feature, obtaining expressions for the amount of sharpening and identifying how spurious structures appear. Illustrative examples are provided. These results enhance the utility of this widely used deconvolution approach to spectral analysis.
format Online
Article
Text
id pubmed-9497885
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-94978852022-09-23 Decoding ‘Maximum Entropy’ Deconvolution Le, Long V. Kim, Tae Jung Kim, Young Dong Aspnes, David E. Entropy (Basel) Article For over five decades, the mathematical procedure termed “maximum entropy” (M-E) has been used to deconvolve structure in spectra, optical and otherwise, although quantitative measures of performance remain unknown. Here, we examine this procedure analytically for the lowest two orders for a Lorentzian feature, obtaining expressions for the amount of sharpening and identifying how spurious structures appear. Illustrative examples are provided. These results enhance the utility of this widely used deconvolution approach to spectral analysis. MDPI 2022-09-02 /pmc/articles/PMC9497885/ /pubmed/36141124 http://dx.doi.org/10.3390/e24091238 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Le, Long V.
Kim, Tae Jung
Kim, Young Dong
Aspnes, David E.
Decoding ‘Maximum Entropy’ Deconvolution
title Decoding ‘Maximum Entropy’ Deconvolution
title_full Decoding ‘Maximum Entropy’ Deconvolution
title_fullStr Decoding ‘Maximum Entropy’ Deconvolution
title_full_unstemmed Decoding ‘Maximum Entropy’ Deconvolution
title_short Decoding ‘Maximum Entropy’ Deconvolution
title_sort decoding ‘maximum entropy’ deconvolution
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9497885/
https://www.ncbi.nlm.nih.gov/pubmed/36141124
http://dx.doi.org/10.3390/e24091238
work_keys_str_mv AT lelongv decodingmaximumentropydeconvolution
AT kimtaejung decodingmaximumentropydeconvolution
AT kimyoungdong decodingmaximumentropydeconvolution
AT aspnesdavide decodingmaximumentropydeconvolution

Ejemplares similares