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 background. 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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