Peak Clipping Algorithms for Background Estimation in Spectroscopic Data

In this paper we present sensitive nonlinear iterative peak (SNIP) clipping algorithms to estimate background in various kinds of spectra. We have proposed several improvements of the SNIP algorithm. Moreover, we have extended and generalized the SNIP algorithm for multidimensional coincidence gamma-ray spectra. In addition to the continuous background, the so-called lower-order coincidences, i.e., coincidences peak-background in different dimensions, must also be included into the estimated background. Further, we have derived a set of modifications of the algorithm that allow estimation of specific shapes of background and ridges as well.