期刊
JOURNAL OF MAGNETIC RESONANCE
卷 171, 期 2, 页码 277-283出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jmr.2004.08.007
关键词
covariance spectroscopy; homonuclear 2D NMR spectroscopy; singular value decomposition; principal component analysis; hypercomplex data; states; TPPI; COSY; NOESY
资金
- NIGMS NIH HHS [GM066041] Funding Source: Medline
Covariance NMR is demonstrated for homonuclear 2D NMR data collected using the hypercomplex and TPPI methods. Absorption mode 2D spectra are obtained by application of the square-root operation to the covariance matrices. The resulting spectra closely resemble the 2D Fourier transformation spectra, except that they are fully symmetric with the spectral resolution along both dimensions determined by the favorable resolution achievable along omega(2). An efficient method is introduced for the calculation of the square root of the covariance spectrum by applying a singular value decomposition (SVD) directly to the mixed time-frequency domain data matrix. Applications are shown for 2D NOESY and 2QF-COSY data sets and computational benchmarks are given for data matrix dimensions typically encountered in practice. The SVD implementation makes covariance NMR amenable to routine applications. (C) 2004 Elsevier Inc. All rights reserved.
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