Novel information theory based method of gamma-ray spectra identification

Yin Maowei; Ren Xuemei; Liao Peng; Ren Lixue

doi:10.11884/HPLPB201830.180102

Volume 30 Issue 10

Oct. 2018

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Article Navigation > High Power Laser and Particle Beams > 2018 > 30(10): 106003

Yin Maowei, Ren Xuemei, Liao Peng, et al. Novel information theory based method of gamma-ray spectra identification[J]. High Power Laser and Particle Beams, 2018, 30: 106003. doi: 10.11884/HPLPB201830.180102

Citation:

Yin Maowei, Ren Xuemei, Liao Peng, et al. Novel information theory based method of gamma-ray spectra identification[J]. High Power Laser and Particle Beams, 2018, 30: 106003. doi: 10.11884/HPLPB201830.180102

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Novel information theory based method of gamma-ray spectra identification

doi: 10.11884/HPLPB201830.180102

Key Subject Laboratory of National Defense for Radioactive Waste and Environmental Security, Southwest University of Science and Technology, Mianyang 621010, China

Funds:

National Natural Science Foundation of China 11705154

Defense Industrial Technology Development Program JCKY2017209B010

Sichuan Province Science and Technology Project 2018GZ0196

More Information

Author Bio:
Yin Maowei(1972—), male, PhD, associate professor, engaged in information technology and its application; ymwxk@ustc.edu.cn
Received Date: 2018-04-08
Rev Recd Date: 2018-07-05
Publish Date: 2018-10-15

Abstract

Abstract

In this paper, a relative entropy based method is proposed to identify the gamma-ray spectra of radioactive sources. Firstly, Principal Component Analysis (PCA) algorithm is used to compress data and construct an eigenspace of the gamma-ray spectrum. Then, Randomization Technique (RT) is adopted to normalize the eigenvalue of the gamma-ray spectrum in eigenspace. Hence, the eigenspaces of gamma-ray spectra can be regarded as probability spaces. Finally, the relative entropy of two probability spaces is defined to measure the difference between two contrasted gamma-ray spectra. It was experimentally demonstrated that the proposed method could perform better judgment about the identity of two gamma-ray spectra over most existing methods. The proposed method has the characteristics of less calculation and higher robustness for impact factors of statistic fluctuations, peaks drift and background.
- gamma-ray spectrum,
- identification,
- relative entropy,
- spectrum peak,
- statistic fluctuation

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References(10)

References

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