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Title: Gaussian Mixture Models as Automated Particle Classifiers for Fast Neutron Detectors

Authors:
 [1];  [1];  [1];  [1];  [1];  [1];  [1]
  1. Lawrence Livermore National Laboratory
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1604282
Alternate Identifier(s):
OSTI ID: 1544913
Report Number(s):
[LLNL-JRNL-752600]
[Journal ID: 938753; 938753]
Grant/Contract Number:  
[AC52-07NA27344; DE‐AC52‐07NA27344]
Resource Type:
Accepted Manuscript
Journal Name:
Statistical Analysis and Data Mining
Additional Journal Information:
[ Journal Volume: vol. 12; Journal Issue: no. 6]
Country of Publication:
United States
Language:
English
Subject:
Mathematics and Computing

Citation Formats

Blair, B, Chen, C, Glenn, A, Kaplan, A, Ruz, J, Simms, L, and Wurtz, R. Gaussian Mixture Models as Automated Particle Classifiers for Fast Neutron Detectors. United States: N. p., 2019. Web. doi:10.1002/sam.11432.
Blair, B, Chen, C, Glenn, A, Kaplan, A, Ruz, J, Simms, L, & Wurtz, R. Gaussian Mixture Models as Automated Particle Classifiers for Fast Neutron Detectors. United States. doi:10.1002/sam.11432.
Blair, B, Chen, C, Glenn, A, Kaplan, A, Ruz, J, Simms, L, and Wurtz, R. Thu . "Gaussian Mixture Models as Automated Particle Classifiers for Fast Neutron Detectors". United States. doi:10.1002/sam.11432.
@article{osti_1604282,
title = {Gaussian Mixture Models as Automated Particle Classifiers for Fast Neutron Detectors},
author = {Blair, B and Chen, C and Glenn, A and Kaplan, A and Ruz, J and Simms, L and Wurtz, R},
abstractNote = {},
doi = {10.1002/sam.11432},
journal = {Statistical Analysis and Data Mining},
number = [no. 6],
volume = [vol. 12],
place = {United States},
year = {2019},
month = {7}
}

Journal Article:
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This content will become publicly available on July 25, 2020
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