1990
DOI: 10.1021/ac00204a011
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Combined deconvolution and curve fitting for quantitative analysis of unresolved spectral bands

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Cited by 76 publications
(40 citation statements)
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“…An effective approach to resolve the individual peaks of overlapping bands is the least‐squares curve‐fitting techniques, which calculates an optimized model for the spectrum by use of an iterative procedure to minimize the sum of the squares of the differences between the curve‐fitted spectrum and the data. However, one of the main drawbacks of curve fitting is the appearance of artifacts due to the numerical treatment, when the bands become more overlapped, or the number of overlapped bands increases 26. The most important values for input to the curve‐fitting routine are the number of bands and their positions.…”
Section: Resultsmentioning
confidence: 99%
“…An effective approach to resolve the individual peaks of overlapping bands is the least‐squares curve‐fitting techniques, which calculates an optimized model for the spectrum by use of an iterative procedure to minimize the sum of the squares of the differences between the curve‐fitted spectrum and the data. However, one of the main drawbacks of curve fitting is the appearance of artifacts due to the numerical treatment, when the bands become more overlapped, or the number of overlapped bands increases 26. The most important values for input to the curve‐fitting routine are the number of bands and their positions.…”
Section: Resultsmentioning
confidence: 99%
“…However, since the exact composition of the coal is not known, the selection of parameters, such as the number, position, and width of the bands, is not straightforward. The application of Fourier self-deconvolution, maximum likelihood restoration, and the calculation of derivative spectra has been shown capable of narrowing bandwidths in order to facilitate the selection of these parameters [11,12]. However, these techniques provide poor results for spectra with highly overlapped bands, baseline errors or high noise levels [11,12] Although coal spectra typically exhibit these shortcomings, some of these approaches have been utilized [9,13].…”
Section: E Ft-ir Spectroscopy Methods For Carboxyl and Phenolic Groumentioning
confidence: 99%
“…The application of Fourier self-deconvolution, maximum likelihood restoration, and the calculation of derivative spectra has been shown capable of narrowing bandwidths in order to facilitate the selection of these parameters [11,12]. However, these techniques provide poor results for spectra with highly overlapped bands, baseline errors or high noise levels [11,12] Although coal spectra typically exhibit these shortcomings, some of these approaches have been utilized [9,13]. As an alternative to the approach mentioned above, Solomon et al [14,15] defined a set of 24 Gaussian bands with fixed positions and widths that could reproduce coal spectra within the experimental error.…”
Section: E Ft-ir Spectroscopy Methods For Carboxyl and Phenolic Groumentioning
confidence: 99%
“…[49][50][51][52][53][54][55][56][57][58][59] The combination of deconvolution and curve fitting allows for qualitative as well as quantitative information on complex spectra. [55][56][57][58][59] These recent developments in band analysis techniques have prompted this study of CO adsorbed on Pt/K-LTL. It will be shown that by combined FSD and curve fitting the linear-CO region of the IR spectrum of Pt/K-LTL consists of a larger number of highly overlapped components, which are grouped into a high-and low-frequency region due to the promotion effect of potassium cations.…”
Section: Introductionmentioning
confidence: 99%