Fast NMR spectroscopy reconstruction with a sliding window based Hankel matrix

Nuclear Magnetic Resonance (NMR) spectroscopy is one of the most promising analytical chemistry techniques, although it takes a long time to acquire data. Non-uniform sampling (NUS) is an effective way to reduce the sampling time, but faithful reconstruction methods are needed. The low rank Hankel matrix (LRHM) approach uses the low rank constraint to obtain high-quality spectra from NUS signals, but the reconstruction has a considerable time overhead. In this work, we propose a sliding window based low rank Hankel matrix approach to speed up the spectra reconstruction from NUS signals. Using the sliding window to construct a matrix can effectively reduce the size of the Hankel matrix for faster reconstructions. To further decrease the reconstruction time, parallel computation is applied in the proposed approach. The experiments on both synthetic data and realistic data demonstrate that the reconstruction speed of the proposed method is the fastest among compared methods without sacrificing the quality of spectra. (C) 2022 Elsevier Inc. All rights reserved.

Automated summary

In this study, a sliding window based low rank Hankel matrix approach is proposed to speed up the reconstruction of spectra from non-uniform sampling (NUS) signals. Parallel computation is applied to further reduce the reconstruction time. Experimental results demonstrate that the proposed method achieves the fastest reconstruction speed among compared methods without sacrificing the quality of spectra.