Digital Least Squares Smoothing of Spectra

Abstract

We show that the most significant parameter in digital smoothing of spectra by least squares fitting to a cubic polynomial is the length of the smoothing range, and to avoid loss of resolution we recommend that the smoothing range be chosen approximately 0.7 FWHH (full width at half-height) of the narrowest single lines or components. Multiple use of digital smooths is shown not to be equivalent to a least squares fit of the original data but gives nearly the same response curve in smoothing of Gaussian lines.