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Title:Bayesian algorithms for automated isotope identification
Author(s):Stinnett, Jacob
Advisor(s):Sullivan, Clair Julia
Contributor(s):Meng, Ling Jian
Department / Program:Nuclear, Plasma, & Rad Engr
Discipline:Nuclear, Plasma, Radiolgc Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Bayesian
isotope identification
gamma ray spectroscopy
decision algorithm
Abstract:Handheld radio-isotope identifiers (RIIDs) are widely used in the United States for nuclear security, but these detectors generally have poor performance in isotope identification. While much research is being conducted on alternative detector materials, there is much evidence that the primary problem with these automated identifiers is with the algorithms used for making identifications. We propose a new algorithm using Bayesian statistics that uses peak positions and areas to identify the source while allowing for calibration drift and shielding.
Issue Date:2014-05-30
URI:http://hdl.handle.net/2142/49487
Rights Information:Copyright 2014 Jacob Stinnett
Date Available in IDEALS:2014-05-30
Date Deposited:2014-05


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