Recovery of saturated signal waveform acquired from high-energy particles with artificial neural networks-Reference-Cited by-同舟云学术

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Recovery of saturated signal waveform acquired from high-energy particles with artificial neural networks

Published:2019-09-30 Issue:10 Volume:30 Page:
ISSN:1001-8042
Container-title:Nuclear Science and Techniques
language:en
Short-container-title:NUCL SCI TECH

Author:

Liu Yu,Zhu Jing-Jun,Roberts Neil,Chen Ke-Ming,Yan Yu-Lu,Mo Shuang-Rong,Gu Peng,Xing Hao-Yang

Publisher

Springer Science and Business Media LLC

Subject

Nuclear Energy and Engineering,Nuclear and High Energy Physics

Link

http://link.springer.com/content/pdf/10.1007/s41365-019-0677-0.pdf

Reference31 articles.

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2. X.B. Xie, Recover certain low-frequency information for full waveform inversion. SEG Tech. Prog. Expand. Abstr. 2013, 1053–1057 (2019). https://doi.org/10.1190/segam2013-0451.1

3. D.W. Huang, J.H. Yang, D.J. Zhou et al., Recovering an unknown signal completely submerged in strong noise by a new stochastic resonance method. Commun. Nonlinear Sci. 66, 156–166 (2019). https://doi.org/10.1016/j.cnsns.2018.06.011

4. S. Marrone, D. Cano-Ott, N. Colonna et al., Pulse shape analysis of liquid scintillators for neutron studies. Nucl. Instrum. Methods Phys. Res. Sect. A 490, 299–307 (2002). https://doi.org/10.1016/s0168-9002(02)01063-x

5. M. Cavallaro, S. Tropea, C. Agodi et al., Pulse-shape discrimination in NE213 liquid scintillator detectors. Nucl. Instrum. Methods Phys. Res. Sect. A 700, 65–69 (2013). https://doi.org/10.1016/j.nima.2012.10.056

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