%0 Journal Article
%T Signal recognition efficiencies of artificial neural-network pulse-shape discrimination in HPGe $0¦Í¦Â¦Â$-decay searches
%A A. Caldwell
%A F. Cossavella
%A B. Majorovits
%A D. Palioselitis
%A O. Volynets
%J Physics
%D 2014
%I arXiv
%R 10.1140/epjc/s10052-015-3573-8
%X A pulse-shape discrimination method based on artificial neural networks was applied to pulses simulated for different background, signal and signal-like interactions inside a germanium detector. The simulated pulses were used to investigate variations of efficiencies as a function of used training set. It is verified that neural networks are well-suited to identify background pulses in true-coaxial high-purity germanium detectors. The systematic uncertainty on the signal recognition efficiency derived using signal-like evaluation samples from calibration measurements is estimated to be 5\%. This uncertainty is due to differences between signal and calibration samples.
%U http://arxiv.org/abs/1412.0895v3