We have developed a novel noise-minimization method that is applicable to all kinds of spectral data, which introduces little distortion in the signal waveform. It is based on the singular value decomposition of a matrix and is an advanced version of the conventional method for minimizing the background noise from a line spectrum, the details of which we reported in a previous paper [Appl. Spectrosc. 48, 1453 (1994).]. In order to cope with a continuum spectrum, we have calculated a difference spectrum between an observed spectrum and a smoothed one. After minimizing noise components from the difference spectrum by the use of the previous method, we add it to the smoothed spectrum. We also propose a method for reducing the computation time by introducing a data-division technique. Noise minimization for an infrared absorption spectrum of polystyrene is shown.
Tetsuo Iwata and Jun Koshoubu, "Minimization of Noise in Spectral Data," Appl. Spectrosc. 50, 747-752 (1996)
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