- Tytuł:
- Pulse shape discrimination of neutrons and gamma rays using kohonen artificial neural networks
- Autorzy:
-
Tambouratzis, T.
Chernikova, D.
Pzsit, I. - Powiązania:
- https://bibliotekanauki.pl/articles/91759.pdf
- Data publikacji:
- 2013
- Wydawca:
- Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
- Tematy:
-
shape
neutron
discrimination
gamma rays
Kohonen artificial neural networks
ANNs
linear vector quantisation
LVQ
self-organizing map
SOM
pulse shape discrimination
PSD - Opis:
- The potential of two Kohonen artificial neural networks (ANNs) - linear vector quantisation (LVQ) and the self organising map (SOM) - is explored for pulse shape discrimination (PSD), i.e. for distinguishing between neutrons (n’s) and gamma rays (’s). The effect that (a) the energy level, and (b) the relative size of the training and test sets, have on identification accuracy is also evaluated on the given PSD dataset. The two Kohonen ANNs demonstrate complementary discrimination ability on the training and test sets: while the LVQ is consistently more accurate on classifying the training set, the SOM exhibits higher n/ identification rates when classifying new patterns regardless of the proportion of training and test set patterns at the different energy levels; the average time for decision making equals ˜100 μs in the case of the LVQ and ˜450 μs in the case of the SOM.
- Źródło:
-
Journal of Artificial Intelligence and Soft Computing Research; 2013, 3, 2; 77-88
2083-2567
2449-6499 - Pojawia się w:
- Journal of Artificial Intelligence and Soft Computing Research
- Dostawca treści:
- Biblioteka Nauki
Artykuł