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[학술저널]

  • 학술저널

원영도 김대성 원호식

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Singular value decomposition (SVD) has been used during past few decades in the advanced NMR data processing and in many applicable areas. A new modified SVD, piecewise polynomial truncated SVD (PPTSVD) was developed for the large solvent peak suppression and noise elimination in NMR signal processing. PPTSVD consists of two algorithms of truncated SVD (TSVD) and L1 problems. In TSVD, some unwanted large solvent peaks and noises are suppressed with a certain soft threshold value while signal and noise in raw data are resolved and eliminated out in L1 problem routine. The advantage of the current PPTSVD method compared to many SVD methods is to give the better S/N ratio in spectrum, and less time consuming job that can be applicable to multidimensional NMR data processing.

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