We describe the incorporation of non-uniform sampling (NUS) compressed sensing (CS) into oriented sample (OS) solid-state NMR for stationary aligned samples and magic angle spinning (MAS) Solid-state NMR for unoriented 'powder' samples. Both simulated and experimental results indicate that 25-33\% of a full linearly sampled data set is required to reconstruct two- and three-dimensional solid-state NMR spectra with high fidelity. A modest increase in signal-to-noise ratio accompanies the reconstruction.
%0 Journal Article
%1 lin_sampling_2013
%A Lin, Eugene C
%A Opella, Stanley J
%D 2013
%J J. Magn. Reson.
%K Algorithms,Compressed Distribution,Powders,Protein Interpretation,Magnetic NMR,Reproducibility NMR,Statistical Proteins,Non-uniform Ratio,Solid-state Resonance Results,Sensitivity,Signal-To-Noise Simulation,Data Spectroscopy,Membrane of samples,Poisson sampling,Oriented sensing,Computer
%P 40--48
%R 10.1016/j.jmr.2013.09.013
%T Sampling scheme and compressed sensing applied to solid-state \NMR\ spectroscopy
%V 237
%X We describe the incorporation of non-uniform sampling (NUS) compressed sensing (CS) into oriented sample (OS) solid-state NMR for stationary aligned samples and magic angle spinning (MAS) Solid-state NMR for unoriented 'powder' samples. Both simulated and experimental results indicate that 25-33\% of a full linearly sampled data set is required to reconstruct two- and three-dimensional solid-state NMR spectra with high fidelity. A modest increase in signal-to-noise ratio accompanies the reconstruction.
@article{lin_sampling_2013,
abstract = {We describe the incorporation of non-uniform sampling (NUS) compressed sensing (CS) into oriented sample (OS) solid-state NMR for stationary aligned samples and magic angle spinning (MAS) Solid-state NMR for unoriented 'powder' samples. Both simulated and experimental results indicate that 25-33{\%} of a full linearly sampled data set is required to reconstruct two- and three-dimensional solid-state NMR spectra with high fidelity. A modest increase in signal-to-noise ratio accompanies the reconstruction.},
added-at = {2017-03-14T02:48:56.000+0100},
author = {Lin, Eugene C and Opella, Stanley J},
biburl = {https://www.bibsonomy.org/bibtex/29d9e03f280097633012b573c5b4c1a85/nmrresource},
doi = {10.1016/j.jmr.2013.09.013},
interhash = {cbf0b90bb6568aba91868d08a8ced99d},
intrahash = {9d9e03f280097633012b573c5b4c1a85},
issn = {1096-0856},
journal = {J. Magn. Reson.},
keywords = {Algorithms,Compressed Distribution,Powders,Protein Interpretation,Magnetic NMR,Reproducibility NMR,Statistical Proteins,Non-uniform Ratio,Solid-state Resonance Results,Sensitivity,Signal-To-Noise Simulation,Data Spectroscopy,Membrane of samples,Poisson sampling,Oriented sensing,Computer},
month = dec,
pages = {40--48},
pmid = {24140622},
timestamp = {2017-03-14T02:49:21.000+0100},
title = {{Sampling scheme and compressed sensing applied to solid-state {\{}NMR{\}} spectroscopy}},
volume = 237,
year = 2013
}