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Activity Number:
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191
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Type:
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Contributed
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Date/Time:
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Monday, August 4, 2008 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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| Abstract - #301471 |
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Title:
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Smoothing Spectral Data
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Author(s):
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Tom Burr*+ and Scott Garner and Nicolas Hengartner and Steve Myers
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Companies:
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Los Alamos National Laboratory and Los Alamos National Laboratory and Los Alamos National Laboratory and Los Alamos National Laboratory
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Address:
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Mail Stop F600, Los Alamos , NM, 87545,
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Keywords:
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smoothing ; isotope identification ; spectral
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Abstract:
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The energy spectra of gamma-rays emitted by radioisotopes act as finger prints that enable identification of the source. Such identification from low-resolution NaI detectors over short time periods is challenging for several reasons, including the Poisson fluctuations in the recorded counts. Smoothing the data over neighboring energy bins can reduce the noise in the raw counts, at the cost of introducing a bias that de-emphasizes the peaks and valleys of the spectrum. This paper describes a new two-stage smoothing procedure that uses a multiplicative bias correction procedure suitable for adjusting initial smoothed spectra. We illustrate the benefit of this new method on example spectra for several smoothing options and indicate potential improvements for radio-isotope identification.
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