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국가지식-학술정보

Noise Suppression of NMR Signal by Piecewise Polynomial Truncated Singular Value Decomposition

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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 far the large solvent peak suppression and noise elimination in U signal processing. PPTSVD consists of two algorithms of truncated SVD (TSVD) and L<TEX>$_1$</TEX> problems. In TSVD, some unwanted large solvent peaks and noises are suppressed with a certain son threshold value while signal and noise in raw data are resolved and eliminated out in L<TEX>$_1$</TEX> 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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