Chen Jianhan, De Angelis Anna A, Mandelshtam Vladimir A, Shaka A J
Chemistry Department, University of California at Irvine, Irvine, CA 92697-2025, USA.
J Magn Reson. 2003 May;162(1):74-89. doi: 10.1016/s1090-7807(03)00045-4.
An efficient way to treat two-dimensional (2D) constant-time (CT) NMR data using the filter diagonalization method (FDM) is presented. In this scheme a pair of N- and P-type data sets from a 2D CT NMR experiment are processed jointly by FDM as a single data set, twice as large, in which the signal effectively evolves in time for twice as long. This scheme is related to "mirror-image" linear prediction, but with the distinction that the data are directly used, without any preprocessing such as Fourier transformation along one dimension, or point-by-point reflection. As the signal has nearly perfect Lorentzian line shape in the CT dimension, it can be efficiently handled by the FDM approach. Applied to model and experimental signals, the scheme shows significant resolution improvement, and appears to tolerate noise reasonably well. Other complex aspects of multidimensional FDM are discussed and illustrated.
本文提出了一种使用滤波器对角化方法（FDM）处理二维（2D）恒时（CT）核磁共振数据的有效方法。在该方案中，来自二维CT核磁共振实验的一对N型和P型数据集由FDM作为一个两倍大的单个数据集联合处理，其中信号在时间上有效地演化两倍长。该方案与“镜像”线性预测有关，但区别在于直接使用数据，无需任何预处理，如沿一个维度的傅里叶变换或逐点反射。由于信号在CT维度上具有近乎完美的洛伦兹线形，因此可以通过FDM方法有效地处理。应用于模型信号和实验信号时，该方案显示出显著的分辨率提高，并且似乎对噪声具有较好的耐受性。还讨论并说明了多维FDM的其他复杂方面。
