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