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Large Solvent and Noise Peak Suppression by Combined SVD-Harr Wavelet Transform

Title
Large Solvent and Noise Peak Suppression by Combined SVD-Harr Wavelet Transform
Author
원호식
Keywords
NMR; Singular value decomposition; Harr Wavelet; Peak suppression
Issue Date
2003-07
Publisher
Korean Chemical Society (대한화학회)
Citation
Bulletin of the Korean Chemical Society, v. 24, issue. 7, page. 971-974
Abstract
By utilizing singular value decomposition (SVD) and shift averaged Harr wavelet transform (WT) with a set of Daubechies wavelet coefficients (1/2, -1/2), a method that can simultaneously eliminate an unwanted large solvent peak and noise peaks from NMR data has been developed. Noise elimination was accomplished by shift-averaging the time domain NMR data after a large solvent peak was suppressed by SVD. The algorithms took advantage of the WT, giving excellent results for the noise elimination in the Gaussian type NMR spectral lines of NMR data pretreated with SVD, providing superb results in the adjustment of phase and magnitude of the spectrum. SVD and shift averaged Haar wavelet methods were quantitatively evaluated in terms of threshold values and signal to noise (S/N) ratio values.
URI
http://koreascience.or.kr/article/JAKO200302727293734.pagehttps://repository.hanyang.ac.kr/handle/20.500.11754/156045
ISSN
0253-2964; 1229-5949
DOI
10.5012/bkcs.2003.24.7.971
Appears in Collections:
COLLEGE OF SCIENCE AND CONVERGENCE TECHNOLOGY[E](과학기술융합대학) > CHEMICAL AND MOLECULAR ENGINEERING(화학분자공학과) > Articles
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