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@inproceedings{1378041, author = {Amiri, Moslem and Přenosil, Václav and Cvachovec, František}, address = {Lisbon}, booktitle = {2015 4th International Conference on Advancements in Nuclear Instrumentation Measurement Methods and their Applications (ANIMMA)}, doi = {http://dx.doi.org/10.1109/ANIMMA.2015.7465553}, keywords = {organic scintillator; counter; statistical test; measures of fit; neutron spectroscopy}, howpublished = {elektronická verze "online"}, language = {eng}, location = {Lisbon}, isbn = {978-1-4799-9918-7}, pages = {1-5}, publisher = {IEEE}, title = {Neutron/gamma-ray discrimination through measures of fit}, year = {2016} }
TY - JOUR ID - 1378041 AU - Amiri, Moslem - Přenosil, Václav - Cvachovec, František PY - 2016 TI - Neutron/gamma-ray discrimination through measures of fit PB - IEEE CY - Lisbon SN - 9781479999187 KW - organic scintillator KW - counter KW - statistical test KW - measures of fit KW - neutron spectroscopy N2 - Statistical tests and their underlying measures of fit can be utilized to separate neutron/gamma-ray pulses in a mixed radiation field. In this article, first the application of a sample statistical test is explained. Fit measurement-based methods require true pulse shapes to be used as reference for discrimination. This requirement makes practical implementation of these methods difficult; typically another discrimination approach should be employed to capture samples of neutrons and gamma-rays before running the fit-based technique. In this article, we also propose a technique to eliminate this requirement. These approaches are applied to several sets of mixed neutron and gamma-ray pulses obtained through different digitizers using stilbene scintillator in order to analyze them and measure their discrimination quality. ER -
AMIRI, Moslem, Václav PŘENOSIL and František CVACHOVEC. Neutron/gamma-ray discrimination through measures of fit. In \textit{2015 4th International Conference on Advancements in Nuclear Instrumentation Measurement Methods and their Applications (ANIMMA)}. Lisbon: IEEE, 2016. p.~1-5. ISBN~978-1-4799-9918-7. doi:10.1109/ANIMMA.2015.7465553.
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