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Accelerated NMR Spectroscopy with Low‐Rank Reconstruction
Author(s) -
Qu Xiaobo,
Mayzel Maxim,
Cai JianFeng,
Chen Zhong,
Orekhov Vladislav
Publication year - 2015
Publication title -
angewandte chemie
Language(s) - English
Resource type - Journals
eISSN - 1521-3757
pISSN - 0044-8249
DOI - 10.1002/ange.201409291
Subject(s) - rank (graph theory) , signal (programming language) , sampling (signal processing) , sensitivity (control systems) , nuclear magnetic resonance spectroscopy , spectroscopy , field (mathematics) , sample (material) , computer science , property (philosophy) , signal processing , biological system , chemistry , materials science , mathematics , physics , electronic engineering , detector , engineering , digital signal processing , telecommunications , organic chemistry , combinatorics , philosophy , biology , epistemology , chromatography , quantum mechanics , programming language , pure mathematics , computer hardware
Accelerated multi‐dimensional NMR spectroscopy is a prerequisite for high‐throughput applications, studying short‐lived molecular systems and monitoring chemical reactions in real time. Non‐uniform sampling is a common approach to reduce the measurement time. Here, a new method for high‐quality spectra reconstruction from non‐uniformly sampled data is introduced, which is based on recent developments in the field of signal processing theory and uses the so far unexploited general property of the NMR signal, its low rank. Using experimental and simulated data, we demonstrate that the low‐rank reconstruction is a viable alternative to the current state‐of‐the‐art technique compressed sensing. In particular, the low‐rank approach is good in preserving of low‐intensity broad peaks, and thus increases the effective sensitivity in the reconstructed spectra.