dSINC proposes an alternative algorithm for waveform discrimination of measurement data from multi-layer scintillator sandwich designs. dSINC attempts to solve problems related to noise and peaks-piling sensitivity in the feature extraction step of traditional KNN waveform discrimination, by fitting the derivative of the entire gain section of the waveform against ideal waveforms learned from training data and thereby completely sidestepping the problems of feature extraction.
