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Wei ZHANG (张伟), Tongyu WU (吴彤宇), Bowen ZHENG (郑博文), Shiping LI (李世平), Yipo ZHANG (张轶泼), Zejie YIN (阴泽杰). A real-time neutron-gamma discriminator based on the support vector machine method for the time-of-fiight neutron spectrometer[J]. Plasma Science and Technology, 2018, 20(4): 45601-045601. DOI: 10.1088/2058-6272/aaaaa9
Citation: Wei ZHANG (张伟), Tongyu WU (吴彤宇), Bowen ZHENG (郑博文), Shiping LI (李世平), Yipo ZHANG (张轶泼), Zejie YIN (阴泽杰). A real-time neutron-gamma discriminator based on the support vector machine method for the time-of-fiight neutron spectrometer[J]. Plasma Science and Technology, 2018, 20(4): 45601-045601. DOI: 10.1088/2058-6272/aaaaa9

A real-time neutron-gamma discriminator based on the support vector machine method for the time-of-fiight neutron spectrometer

Funds: This work was partially supported by the National Science and Technology Major Project of Ministry of Science and Technology of China (Grant Nos. 2014GB109003 and 2015GB111002) and National Natural Science Foundation of China (Grant Nos. 11375195, 11575184, 11375004 and 11775068).
More Information
  • Received Date: August 30, 2017
  • A new neutron-gamma discriminator based on the support vector machine (SVM) method is proposed to improve the performance of the time-of-fiight neutron spectrometer. The neutron detector is an EJ-299-33 plastic scintillator with pulse-shape discrimination (PSD) property. The SVM algorithm is implemented in field programmable gate array (FPGA) to carry out the real-time sifting of neutrons in neutron-gamma mixed radiation fields. This study compares the ability of the pulse gradient analysis method and the SVM method. The results show that this SVM discriminator can provide a better discrimination accuracy of 99.1%. The accuracy and performance of the SVM discriminator based on FPGA have been evaluated in the experiments. It can get a figure of merit of 1.30.
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