Modeling NMR Lineshapes Using Logspline Density Functions |
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Authors: | Jonathan Raz Erik J. Fernandez John Gillespie |
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Affiliation: | aDepartment of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan, 48109-202;bDepartment of Chemical Engineering, University of Virginia, Charlottesville, Virginia, 22903;cDepartment of Mathematics and Statistics, University of Michigan, Dearborn, Michigan, 48128-1491 |
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Abstract: | Distortions in the FID and spin echo due to magnetic field inhomogeneity are proved to have a representation as the characteristic function of some probability distribution. In the special case that the distribution is Cauchy, the model reduces to the conventional Lorentzian model. A more general and flexible representation is presented using the Fourier transform of a logspline density. An algorithm for fitting the model is described, the performance of the model and algorithm is investigated in applications to real and simulated data sets, and the logspline approach is compared to a previous Hermitian spline approach and to the Lorentzian model. The logspline model is more parsimonious than the Hermitian spline model, provides a better fit to real data, and is much less biased than the Lorentzian model. |
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