Open AccessEvaluation on least square method applied to gamma spectrum de-noising
Author(s) -
Fēi Li,
Xinle Lang,
Yi Chen,
Liangquan Ge,
Feng Li,
Siwei Li
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1423/1/012002
Subject(s) - nuclide , spectrum (functional analysis) , noise (video) , detector , noise reduction , reduction (mathematics) , algorithm , energy (signal processing) , gamma ray , spectral density , physics , computer science , mathematics , statistics , optics , nuclear physics , artificial intelligence , geometry , quantum mechanics , image (mathematics)
Gamma energy spectrum is a way to confirm the type and content of radioactive nuclides in substances. In order to obtain effective data of gamma spectrum, it is necessary to analyze the data of gamma spectrum obtained by the detector. Nevertheless, due to the influence of statistical fluctuation and gamma generated by the environment itself during the measurement of gamma spectrum, the obtained gamma spectrum is not accurate enough as a result of needing spectral analysis of gamma spectrum, and noise reduction can make the spectral data smoother. Therefore, this paper studies the noise reduction algorithm for gamma spectrum analysis, analyzes the design and application of different algorithms in the process of noise reduction, and summarizes the advantages and disadvantages of this algorithm and others.