An artificial neural network based neutron–gamma discrimination and pile-up rejection framework for the BC-501 liquid scintillation detector-Reference-Cited by-同舟云学术

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An artificial neural network based neutron–gamma discrimination and pile-up rejection framework for the BC-501 liquid scintillation detector

Published:2009-11 Issue:2 Volume:610 Page:534-539
ISSN:0168-9002
Container-title:Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
language:en
Short-container-title:Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

Author:

Ronchi E.,Söderström P.-A.,Nyberg J.,Andersson Sundén E.,Conroy S.,Ericsson G.,Hellesen C.,Gatu Johnson M.,Weiszflog M.

Publisher

Elsevier BV

Subject

Instrumentation,Nuclear and High Energy Physics

Reference13 articles.

1. BC501, BC501A and BC519 scintillation detectors data sheet 〈http://www.detectors.saint-gobain.com/〉.

2. An analytical approach to the evaluation of the pulse shape discrimination properties of scintillators

3. Digital pulse-shape discrimination of fast neutrons and rays

4. A 2π neutron and γ-ray multiplicity filter for the NORDBALL detection system

5. TNT digital pulse processor

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