论文标题
审查和前景：NMR光谱降级和重建，低等级Hankel矩阵和张量
Review and Prospect: NMR Spectroscopy Denoising & Reconstruction with Low Rank Hankel Matrices and Tensors
论文作者
论文摘要
核磁共振（NMR）光谱是化学，生物学和生命科学方面的重要分析工具，但其敏感性相对较低和较长的获取时间。因此，提高明显的信噪比和加速数据采集是必不可少的。在这篇综述中，我们总结了低等级Hankel矩阵和张量方法的最新进展，这些方法利用了自由感应衰减信号的指数特性，以实现有效的DeNoSising和Spectra重建。我们还概述了未来的发展，这些发展可能会使NMR光谱学成为更强大的技术。
Nuclear Magnetic Resonance (NMR) spectroscopy is an important analytical tool in chemistry, biology, and life science, but it suffers from relatively low sensitivity and long acquisition time. Thus, improving the apparent signal-to-noise ratio and accelerating data acquisition become indispensable. In this review, we summarize the recent progress on low rank Hankel matrix and tensor methods, that exploit the exponential property of free induction decay signals, to enable effective denoising and spectra reconstruction. We also outline future developments that are likely to make NMR spectroscopy a far more powerful technique.
