1990
DOI: 10.1021/ac00205a007
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General least-squares smoothing and differentiation by the convolution (Savitzky-Golay) method

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Cited by 581 publications
(249 citation statements)
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“…A procedure to compute the convolution weights h j is given by Gorry (1990), the method allows considering also the end points of the data set. In the present case, the smoothing was performed using 7 points (m = 3).…”
Section: Numerical Validationmentioning
confidence: 99%
“…A procedure to compute the convolution weights h j is given by Gorry (1990), the method allows considering also the end points of the data set. In the present case, the smoothing was performed using 7 points (m = 3).…”
Section: Numerical Validationmentioning
confidence: 99%
“…In this study, in order to reduce the spectral noise, baseline drift, and the interference from other backgrounds as well as distinguish overlapping peaks, five preprocessing methods were applied to improve spectral resolution, sensitivity, and the signal-to-noise ratio of the spectra [25]. Among them, the Savitzky-Golay (S-G) smoothing algorithm uses a weighted average method to quantize the data in the moving window by polynomial least squares fitting as well as emphasizes the central role of the center point [26].…”
Section: Spectral Preprocessing Methodsmentioning
confidence: 99%
“…In general, filters based on least squares minimization are known as Savitzky-Golay filters, cf. [12,13]. It is not only the stability, but also robustness and accuracy of the meshless method is then affected by the WLSQ filter.…”
Section: Numerical Filteringmentioning
confidence: 99%
“…[12,13]. The WLSQ filtration technique serves primarily for the stabilization of the numerical scheme and can be utilized under the assumption that the governing equations are linear and the solution is smooth enough.…”
Section: Introductionmentioning
confidence: 99%