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Noise reduction in prompt gamma spectra acquired in short times
- Im, Hee-Jung;
- Lee, Yun-Hee;
- Park, Yong Joon;
- Song, Byoung Chul;
- Cho, JungHwan;
- 외 1명
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Principal component analysis was applied for a noise reduction in prompt gamma spectra, especially acquired in short times, with the aim of improving signal-to-noise ratio. After the noise reduction, relevant information was preserved in the models while discarding much of the noise, and the signal-to-noise ratio was enhanced in the noisy prompt gamma spectra measured for 20 s. History data, which has multi elements and accurate peak positions of interest with a long enough measurement time, should be prepared for an effective noise reduction. (C) 2007 Elsevier B.V. All rights reserved.
키워드
prompt gamma-ray neutron activation analysis (PGNAA); gamma spectra; principal component analysis (PCA); noise reduction; signal-to-noise (S/N); NEUTRON; SPECTROSCOPY
- 제목
- Noise reduction in prompt gamma spectra acquired in short times
- 저자
- Im, Hee-Jung; Lee, Yun-Hee; Park, Yong Joon; Song, Byoung Chul; Cho, JungHwan; Kim, Won-Ho
- 발행일
- 2007-05
- 유형
- Article
- 권
- 574
- 호
- 2
- 페이지
- 272 ~ 279