Abstract

The determination of the parameters characterizing line profiles embedded in a noisy spectrum is an important task in IR and Raman spectroscopy. A direct analysis from an inspection of the spectrum is often difficult in the presence of overlapped profiles and/or considerable back-ground. This paper presents an algorithm based on alternate stages of linear and nonlinear optimization for extracting Lorentzians or Gaussians from the measured data, taking into account the presence of a frequency-dependent background superimposed onto white noise. The analysis of several experimental spectra shows the capability of the algorithm in discriminating noisy and partially overlapped profiles.

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