A novel detection-estimation scheme for noisy NMR signals: Applications to delayed acquisition data
A novel detection-estimation scheme for noisy NMR signals: Applications to delayed acquisition data
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DOI：
10.1006/jmre.1997.1215
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发表时间：
1997-09-01
影响因子：
2.2
通讯作者：
Pines, A
中科院分区：
文献类型：
--
作者：
Lin, YY;Hodgkinson, P;Pines, A
许多潜在的有趣的和有用的类NMR实验产生的数据，传统的频谱估计和量化aa傅立叶变换是不满意的。特别是，最近推出的固态NMR实验，涉及长时间的延迟之前，数据采集属于这一类，因为自由感应衰减严重“截断"，并具有低的信号-噪声比。介绍了一种新的检测-估计方案，以便分析来自这样的实验和其他实验的数据，其中灵敏度低和/或数据记录被强阻尼或截断。基于指数数据建模的假设，首先使用从信息论导出的准则检测存在的信号的数量，然后使用矩阵束方法估计谱参数，蒙特卡罗模拟和实验。应用程序进行，以证明其上级的统计和计算性能和延迟采集数据的一般适用性。在调查的范围内的注意水平，它被发现，这种方法基本上是接近最优的意义上说，估计的频谱参数的偏差几乎等于零和方差非常接近其理论Cramer-Rao下限。与目前流行的奇异值分解线性预测方法相比，该方法不仅在较低的“击穿”信噪比阈值（约1.5dB）下提高了估计精度（约2-4倍），而且计算量降低了约一个数量级，在有效减少截断伪影方面也有很大的前景。本文的结论是，这种方法不仅方便了延迟采集数据的分析，而且可以成为常规NMR谱定量的一种有价值的工具。(C)北京：科学出版社.
Many potentially interesting and useful classes of NMR experiments generate data for which conventional spectral estimation and quantification aa the Fourier transform are unsatisfactory. In particular, recently introduced solid-state NMR experiments which involve long delays before data acquisition fall into this category, as the free induction decays are heavily ''truncated'' and have low signal-to-noise ratios. A novel detection-estimation scheme is introduced in order to analyze data from such experiments and others where the sensitivity is low and/or the data record is strongly damped or truncated, Based on the assumption of exponential data modeling, the number of signals present is first detected using criteria derived from information theory and the spectral parameters are then estimated using the matrix pencil method, Monte Carlo simulations and experimental. applications are carried out to demonstrate its superior statistical and computational performances and its general applicability to delayed acquisition data. Over the range of note levels investigated, it is found that this approach is essentially near-optimal in the sense that the estimated spectral parameters have biases almost equal to zero and variances very close to their theoretical Cramer-Rao lower bounds. Compared to the popular method of linear prediction with singular value decomposition, this method not only improves the estimation accuracy (by a factor of 2-4) with a lower ''break-down'' signal-to-noise threshold (approximate to 1.5 dB), but also reduces the computational cost by about an order of magnitude, It also holds great promise in effectively reducing truncation artifacts. It is concluded that this approach not only facilitates the analysis of delayed acquisition data, but can also become a valuable tool in the routine quantification of general NMR spectra, ia listing of programs is also included in the Appendix. (C) 1997 Academic Press.