1991
DOI: 10.1016/0020-0891(91)90015-8
|View full text |Cite
|
Sign up to set email alerts
|

Deconvolution of Fabry-Perot spectra

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
2
0

Year Published

1993
1993
2019
2019

Publication Types

Select...
5

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(2 citation statements)
references
References 9 publications
0
2
0
Order By: Relevance
“…Accurate analysis of the 2-D intensity pattern measured by the instrument is important for interpreting profiles of spectral lines. A variety of algorithms have been developed to deconvolve the input spectrum from the interferometric measurement, but they rely on assumptions made about the shape (e.g., Gaussian, Lorentzian, Voigt functions) of the source spectrum [10,11,12]. Other techniques include analysis in the Fourier domain, which also assumes a known source distribution [13].…”
Section: Introductionmentioning
confidence: 99%
“…Accurate analysis of the 2-D intensity pattern measured by the instrument is important for interpreting profiles of spectral lines. A variety of algorithms have been developed to deconvolve the input spectrum from the interferometric measurement, but they rely on assumptions made about the shape (e.g., Gaussian, Lorentzian, Voigt functions) of the source spectrum [10,11,12]. Other techniques include analysis in the Fourier domain, which also assumes a known source distribution [13].…”
Section: Introductionmentioning
confidence: 99%
“…The utility of maximum entropy (and the closely related maximum likelihood) has been demonstrated for deconvolution and smoothing in a number of spectroscopic techniques, particularly in NMR, but it is still not a widely applied technique. While there are other methods that yield comparable results for particular applications, the maximum entropy approach has proven to be particularly robust and generally provides results as good as or superior to other methods. This broad range of application is achieved at the expense of increased computational time, but given the increasing power of desktop workstations, it seems likely that the use of maximum entropy methods will continue to expand. To our knowledge, maximum entropy has not been previously applied to the problem of baseline correction.…”
mentioning
confidence: 99%