Automated wavelet analysis of low resolution gamma-ray spectra and peak area uncertainty
Xiong, Hao
Loading…
Permalink
https://hdl.handle.net/2142/78576
Description
Title
Automated wavelet analysis of low resolution gamma-ray spectra and peak area uncertainty
Author(s)
Xiong, Hao
Issue Date
2015-05-01
Department of Study
Nuclear, Plasma, & Rad Engr
Discipline
Nuclear, Plasma, Radiolgc Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
gamma spectrum
automated isotope identification
wavelet analysis
Abstract
The accuracy of automated isotope identification from low resolution gamma-ray spectra can be significantly improved with better algorithms. The method based on the wavelet transform and non-negative least squares (NNLS) are discussed in this thesis. Several improvements are made for the wavelet algorithm itself and different options can be configured in the MATLAB code. The partial or whole spectrum can be sent to NNLS and analyzed with or without subtracting the continuum. The boundary effects are also discussed. Several methods are developed to determine the area uncertainty. The matrix form of wavelet transform and error propagation are used. The inversion of the basis matrix is obtained either by the Moore-Penrose pseudo inversion or by truncated singular value decomposition (TSVD). The results are compared with those given by OriginLab and Gaussian fitting in MATLAB, which are consistent with each other, while TSVD is shown to be more accurate. The wavelet algorithm using TSVD for the area uncertainty calculation works well for complicated spectrum continuum and for overlapping peaks.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
