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The neutrons emitted in heavy-ion fusion-evaporation (HIFE) reactionstogether with the gamma-rays cause unwanted backgrounds in gamma-ray spectra.Especially in the nuclear reactions, where relativistic ion beams (RIBs) areused, these neutrons are serious problem. They have to be rejected in order toobtain clearer gamma-ray peaks. In this study, the radiation energy and threecriteria which were previously determined for separation between neutron andgamma-rays in the HPGe detectors have been used in artificial neural network(ANN) for improving of the decomposition power. According to the preliminaryresults obtained from ANN method, the ratio of neutron rejection has beenimproved by a factor of 1.27 and the ratio of the lost in gamma-rays has beendecreased by a factor of 0.50.

Improvement studies on neutron-gamma separation in HPGe detectors by using neural networks