Fitting sparse Gaussian function mixtures on power spectra

This paper presents a novel method for fitting a sparse Gaussian mixture on a non-negative function of reference. Despite this problem is well known to be highly non-linear, the use of the logarithmic utility function seems to alleviate such an undesired situation. Moreover, sparsity measures related to the Gaussian precision can be integrated in such a way that the numerical algorithm turns out easy to implement, it is numerically efficient, and presents stable convergence. The method has been originally thought for the parameterization of power spectra, but it can also be useful in different scenarios.