Application of singular value decomposition to the analysis of alpha-particle spectra

Singular value decomposition is applied as an alternative matrix inversion method in an iterative algorithm used to fit alpha-particle spectra with nonlinear peak functions. The method is consistently successful, which circumvents code stopping when a singularity appears in an intermediate iteration during the fit procedure. It also provides a diagnosis concerning the origin of the singularity.