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Title: Byzantine Resilient Locally Optimum Radioactive Source Detection Using Collaborative Sensor Networks

Authors:
; ; ; ; ;
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1410077
Report Number(s):
LLNL-CONF-731964
DOE Contract Number:
AC52-07NA27344
Resource Type:
Conference
Resource Relation:
Conference: Presented at: IEEE Global Conference on Signal and Information Processing, Toronto, Canada, Nov 14 - Nov 16, 2017
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; 97 MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY

Citation Formats

Kailkhura, B, Ray, P, Rajan, D, Yen, A, Barnes, P, and Goldhahn, R. Byzantine Resilient Locally Optimum Radioactive Source Detection Using Collaborative Sensor Networks. United States: N. p., 2017. Web.
Kailkhura, B, Ray, P, Rajan, D, Yen, A, Barnes, P, & Goldhahn, R. Byzantine Resilient Locally Optimum Radioactive Source Detection Using Collaborative Sensor Networks. United States.
Kailkhura, B, Ray, P, Rajan, D, Yen, A, Barnes, P, and Goldhahn, R. 2017. "Byzantine Resilient Locally Optimum Radioactive Source Detection Using Collaborative Sensor Networks". United States. doi:. https://www.osti.gov/servlets/purl/1410077.
@article{osti_1410077,
title = {Byzantine Resilient Locally Optimum Radioactive Source Detection Using Collaborative Sensor Networks},
author = {Kailkhura, B and Ray, P and Rajan, D and Yen, A and Barnes, P and Goldhahn, R},
abstractNote = {},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2017,
month = 5
}

Conference:
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