Study of fitting algorithms applied to simultaneous analysis of large numbers of peaks in gamma-ray spectra.

In this paper several nonlinear fitting algorithms without matrix inversion are proposed and investigated. The fitting algorithms represent an integral part of the analysis procedure, allowing us to simultaneously process large numbers of peaks in large blocks of data. The algorithms were applied to the analysis of both one-dimensional as well as two-fold coincidence gamma-ray spectra. The properties of the proposed methods and the suitability of employing the appropriate algorithms to different kinds of gamma-ray spectra were studied.