Non-Uniform Sampling in NMR Spectroscopy and the Preservation of Spectral Knowledge in the Time and Frequency Domains
Non-Uniform Sampling in NMR Spectroscopy and the Preservation of Spectral Knowledge in the Time and Frequency Domains
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DOI：
10.1021/acs.jpca.0c02930
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发表时间：
2020-07-02
影响因子：
2.9
通讯作者：
Mueller，Leonard J.
中科院分区：
文献类型：
--
作者：
Kaur，Manpreet;Lewis，Callie M.;Mueller，Leonard J.
加权非均匀采样（NUS）下的灵敏度增加的证明和量化使用Monte Carlo模拟的核磁共振（NMR）的时域和频域信号。介绍了谱知识的概念，并证明其上级频域信噪比，用于评估核磁共振数据的质量。从理论和数值上证明了两种严格保留谱知识和变换到频域时的时域NUS知识增强的方法。第一，非均匀加权采样使用一致的均方根噪声，适用于采样的奈奎斯特网格上的数据，而第二，块傅立叶变换使用一致的均方根噪声，可用于变换时域数据采集与任意，离网NUS。
The increased sensitivity under weighted non-uniform sampling (NUS) is demonstrated and quantified using Monte Carlo simulations of nuclear magnetic resonance (NMR) time- and frequency-domain signals. The concept of spectral knowledge is introduced and shown to be superior to the frequency-domain signal-to-noise ratio for assessing the quality of NMR data. Two methods for rigorously preserving spectral knowledge and the time-domain NUS knowledge enhancement upon transformation to the frequency domain are demonstrated, both theoretically and numerically. The first, non-uniform weighted sampling using consistent root-mean-square noise, is applicable to data sampled on the Nyquist grid, whereas the second, the block Fourier transform using consistent root-mean-square noise, can be used to transform time-domain data acquired with arbitrary, off-grid NUS.