Photopeak detection and quantification using wavelet analysis

Wavelet Analysis;Non-negative Least Square;Linear Regression;Nuclear Spectrum

Lu, Jie ; Sullivan ; Clair Julia

关键词: Wavelet Analysis;    Non-negative Least Square;    Linear Regression;    Nuclear Spectrum;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/46778/Jie_Lu.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Automated isotope identi cation has long been an important problem inhomeland security and nuclear emergency response. This process is di cultfor low-resolution spectra because of the presence of the Compton contin-uum, electronics noise, and peak overlap. The wavelet transform standsout among many potential solutions of this problem, owing to its ability tode-noise noisy signals, pattern matching, and simultaneous multi-resolutionsignal analysis. In this thesis, a novel wavelet-based algorithm for detectingpeaks and measuring their areas is introduced. Its abilities in locating peaks,resolving overlapping peaks, and determining peak areas are presented andassessed with both simulated signals and real gamma-ray spectra. Peak areauncertainty was explored and future work and directions were discussed atthe end.