2026-09-21T00:25:57Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/46778 2023-07-11 col_2142_5131 col_2142_14837 com_2142_5130 com_2142_14836 com_2142_234

2014-01-16T18:02:14Z 2013-12 2014-01-16T18:02:14Z 2013-12 Sullivan, Clair Julia Lu, Jie 2014-01-16T18:02:14Z Automated isotope identi cation has long been an important problem in homeland security and nuclear emergency response. This process is di cult for low-resolution spectra because of the presence of the Compton contin- uum, electronics noise, and peak overlap. The wavelet transform stands out among many potential solutions of this problem, owing to its ability to de-noise noisy signals, pattern matching, and simultaneous multi-resolution signal analysis. In this thesis, a novel wavelet-based algorithm for detecting peaks and measuring their areas is introduced. Its abilities in locating peaks, resolving overlapping peaks, and determining peak areas are presented and assessed with both simulated signals and real gamma-ray spectra. Peak area uncertainty was explored and future work and directions were discussed at the end. Item withdrawn by Laura Spradlin (lspradl2@illinois.edu) on 2013-12-10T22:09:42Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 ThesisJieLu(Final).pdf: 1968049 bytes, checksum: e1b6ad70a4f57c53c20fa6e0cc9f9269 (MD5) Made available in DSpace on 2014-01-16T18:02:14Z (GMT). No. of bitstreams: 2 Jie_Lu.pdf: 1968344 bytes, checksum: f54f75522be732a9edd5a144ec77821e (MD5) license.txt: 4054 bytes, checksum: 2413624c7156cde7803a10b21436d44f (MD5) http://hdl.handle.net/2142/46778 en Copyright 2013 Jie Lu Wavelet Analysis Non-negative Least Square Linear Regression Nuclear Spectrum Photopeak detection and quantification using wavelet analysis text Nuclear, Plasma, & Rad Engr 1973 Nuclear, Plasma, Radiolgc Engr 5183 University of Illinois at Urbana-Champaign Thesis M.S. MS: Nucl, Plasma, Rad Eng-UIUC 10KS5183MS