Abstract
Abstract This paper shows how the total-least-squares method improves the signal parameter estimates of HSVD, a noniterative black-box method for time-domain NMR data quantification. The algorithm, called HTLS, is presented and discussed. Experiments, performed on simulated and in vivo NMR signals, show the benefits in parameter accuracy that can be obtained from the use of total least squares as compared to ordinary least squares. In particular, the damping factor estimates of spectral components at low signal-to-noise ratios improve substantially, thereby also improving the accuracy of the amplitudes and phases.
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