Bayesian Estimation for Spectral Deconvolution

In this review, we introduce the framework of Bayesian estimation in spectral deconvolution. In Bayesian estimation, we can trace the causal relationships by Bayes’ theorem to extract the underlying structure behind the spectral data. By applying Bayesian estimation to spectral deconvolution, we can...

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Bibliographic Details
Published in:Journal of Surface Analysis 2019, Vol.26(2), pp.130-131
Main Author: Nagata, Kenji
Format: Article
Language:English
Subjects:
Algorithms
Bayesian analysis
Computer simulation
Deconvolution
Monte Carlo simulation
Spectra
Online Access:Get full text
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Summary:In this review, we introduce the framework of Bayesian estimation in spectral deconvolution. In Bayesian estimation, we can trace the causal relationships by Bayes’ theorem to extract the underlying structure behind the spectral data. By applying Bayesian estimation to spectral deconvolution, we can estimate the number of peaks in the spectral data based on the framework of model selection. Furthermore, by using an algorithm called exchange Monte Carlo method, it is possible to solve the problem that is trapped in the local optimum solution.
ISSN:1341-1756
1347-8400
DOI:10.1384/jsa.26.130