Journal article
Detection of radionuclides from weak and poorly resolved spectra using Lasso and subsampling techniques
Radiation measurements, Vol.46(10), pp.1138-1146
10/2011
DOI: 10.1016/j.radmeas.2011.08.020
Abstract
We consider a problem of identification of nuclides from weak and poorly resolved spectra. A two stage algorithm is proposed and tested based on the principle of majority voting. The idea is to model gamma-ray counts as Poisson processes. Then, the average part is taken to be the model and the difference between the observed gamma-ray counts and the average is considered as random noise. In the linear part, the unknown coefficients correspond to if isotopes of interest are present or absent. Lasso types of algorithms are applied to find non-vanishing coefficients. Since Lasso or any prediction error based algorithm is inconsistent with variable selection for finite data length, an estimate of parameter distribution based on subsampling techniques is added in addition to Lasso. Simulation examples are provided in which the traditional peak detection algorithms fail to work and the proposed two stage algorithm performs well in terms of both the False Negative and False Positive errors. ► Identification of nuclides from weak and poorly resolved spectra. ► An algorithm is proposed and tested based on the principle of majority voting. ► Lasso types of algorithms are applied to find non-vanishing coefficients. ► An estimate of parameter distribution based on sub-sampling techniques is included. ► Simulations compare the results of the proposed method with those of peak detection.
Details
- Title: Subtitle
- Detection of radionuclides from weak and poorly resolved spectra using Lasso and subsampling techniques
- Creators
- Er-Wei Bai - Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, USAKung-sik Chan - Department of Statistical and Actuarial Science, University of Iowa, Iowa City, IA 52242, USAWilliam Eichinger - Department of Civil and Environmental Engineering, University of Iowa, Iowa City, IA 52242, USAPaul Kump - Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, USA
- Resource Type
- Journal article
- Publication Details
- Radiation measurements, Vol.46(10), pp.1138-1146
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/j.radmeas.2011.08.020
- ISSN
- 1350-4487
- eISSN
- 1879-0925
- Grant note
- name: DoE, award: DE-FG52-09NA29364
- Language
- English
- Date published
- 10/2011
- Academic Unit
- Civil and Environmental Engineering; Statistics and Actuarial Science; Electrical and Computer Engineering; Radiology
- Record Identifier
- 9983985985002771
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