Spectrometry analysis based on approximation coefficients and deep belief networks

A method of spectrometry analysis based on approximation coefficients and deep belief networks was developed. Detection rate and accurate radionuclide identification distance were used to evaluate the performance of the proposed method in identifying radionuclides. Experimental results show that ide...

Full description

Saved in:
Bibliographic Details
Published in:Nuclear science and techniques 2018-05, Vol.29 (5), p.91-100, Article 69
Main Authors: He, Jian-Ping, Tang, Xiao-Bin, Gong, Pin, Wang, Peng, Han, Zhen-Yang, Yan, Wen, Gao, Le
Format: Article
Language:English
Subjects:
Energy
Hadrons
Heavy Ions
Nuclear Energy
Nuclear Physics
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A method of spectrometry analysis based on approximation coefficients and deep belief networks was developed. Detection rate and accurate radionuclide identification distance were used to evaluate the performance of the proposed method in identifying radionuclides. Experimental results show that identification performance was not affected by detection time, number of radionuclides, or detection distance when the minimum detectable activity of a single radionuclide was satisfied. Moreover, the proposed method could accurately predict isotopic compositions from the spectra of moving radionuclides. Thus, the designed method can be used for radiation monitoring instruments that identify radionuclides.
ISSN:1001-8042
2210-3147
DOI:10.1007/s41365-018-0402-4