Decoding ‘Maximum Entropy’ Deconvolution

Long V. Le; Tae Jung Kim; Young Dong Kim; David E. Aspnes

doi:10.3390/e24091238

Decoding ‘Maximum Entropy’ Deconvolution

Long V. Le, Tae Jung Kim, Young Dong Kim, David E. Aspnes

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

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.

Original language	English
Article number	1238
Journal	Entropy
Volume	24
Issue number	9
DOIs	https://doi.org/10.3390/e24091238
Publication status	Published - Sept 2022

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Publisher Copyright:
© 2022 by the authors.

Keywords

deconvolution
maximum entropy
spectral analysis

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10.3390/e24091238

Cite this

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abstract = "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.",

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AB - 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.

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Decoding ‘Maximum Entropy’ Deconvolution

Abstract

Bibliographical note

Keywords

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