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Estimation method for parameters of overlapping nuclear pulse signal

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Abstract

Identification of nuclear pulse signal is of importance in radioactive measurements, especially in recognizing adjacent overlapping nuclear pulses. In this article, we propose an estimation method for parameters of typical overlapping nuclear pulse signals. First, the nuclear pulses are regarded as individual genes and the norm is set as the fitness function. Second, the global optimal solution is found by searching the population of genetic algorithm, so as to estimate the parameters of nuclear pulse. With high precision, this method can identify parameters of overlapping nuclear pulses in the Sallen–Key Gaussian signal decomposition experiments. This pulse recognition method is of great significance to improve the precision of radioactive measurement and is suitable for serious overlap of nuclear pluses.

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Authors and Affiliations

  1. College of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu, 610059, China

    Hong-Quan Huang, Xiao-Feng Yang, Wei-Cheng Ding & Fang Fang

  2. Fundamental Science on Radioactive Geology and Exploration Technology Laboratory, East China Institute of Technology, Nanchang, 330013, China

    Hong-Quan Huang

Authors
  1. Hong-Quan Huang
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  2. Xiao-Feng Yang
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  3. Wei-Cheng Ding
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  4. Fang Fang
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Corresponding author

Correspondence to Xiao-Feng Yang.

Additional information

This work was supported by the National Natural Science Foundation of China (No. 41204133); Sichuan Province Science and Technology Support Program (No. 2014GZ0020); the Open Science Fund from Key Laboratory of Radioactive Geology and Exploration Technology Fundamental Science for National Defense, East China Institute of Technology(No. RGET1401); and Scientific Research Fund of Sichuan Provincial Education Department (No. 13ZA0066).

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Huang, HQ., Yang, XF., Ding, WC. et al. Estimation method for parameters of overlapping nuclear pulse signal. NUCL SCI TECH 28, 12 (2017). https://doi.org/10.1007/s41365-016-0161-z

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  • DOI: https://doi.org/10.1007/s41365-016-0161-z

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