典型文献
Anti-noise performance of the pulse coupled neural network applied in discrimination of neutron and gamma-ray
文献摘要：
In this study,the anti-noise performance of a pulse-coupled neural network(PCNN)was investigated in the neutron and gamma-ray(n-γ)discrimination field.The experiments were conducted in two groups.In the first group,radiation pulse signals were pre-processed using a Fourier filter to reduce the original noise in the signals,whereas in the second group,the original noise was left untouched to sim-ulate an extremely high-noise scenario.For each part,arti-ficial Gaussian noise with different intensity levels was added to the signals prior to the discrimination process.In the aforementioned conditions,the performance of the PCNN was evaluated and compared with five other commonly used methods of n-γ discrimination:(1)zero crossing,(2)charge comparison,(3)vector projection,(4)falling edge percent-age slope,and(5)frequency gradient analysis.The experi-mental results showed that the PCNN method significantly outperforms other methods with outstanding FoM-value at all noise levels.Furthermore,the fluctuations in FoM-value of PCNN were significantly better than those obtained via other methods at most noise levels and only slightly worse than those obtained via the charge comparison and zero-crossing methods under extreme noise conditions.Addi-tionally,the changing patterns and fluctuations of the FoM-value were evaluated under different noise conditions.Hence,based on the results,the parameter selection strategy of the PCNN was presented.In conclusion,the PCNN method is suitable for use in high-noise application scenarios for n-γ discrimination because of its stability and remark-able discrimination performance.It does not rely on strict parameter settings and can realize satisfactory performance over a wide parameter range.
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作者姓名：
Hao-Ran Liu;Zhuo Zuo;Peng Li;Bing-Qi Liu;Lan Chang;Yu-Cheng Yan
作者机构：
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection,Chengdu University of Technology,Chengdu 610059,China;The Engineering and Technical College of Chengdu University of Technology,Leshan 614000,China;Southwestern Institute of Physics,Chengdu 610225,China;Chengdu University,Chengdu 610106,China
文献出处：
引用格式：
[1]Hao-Ran Liu;Zhuo Zuo;Peng Li;Bing-Qi Liu;Lan Chang;Yu-Cheng Yan-.Anti-noise performance of the pulse coupled neural network applied in discrimination of neutron and gamma-ray)[J].核技术（英文版）,2022(06):89-101
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AB值：
0.511273
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