Abstract
The increased power of nmr as an analytical and structure determining method arises from the development of two-dimensional methods in which spectral maps reflect through-bond and through-space connectivities between atoms. The interpretation of these maps is made complex by many factors, including the large number of such connectivities in many applications, the multiplicity of the spectral elements, and the limited signal-to-noise ratio. As one element of solving these problems, we have developed methods to simplify the cataloging of positions and intensities of peaks, and for examining and selecting among them. Linear Predictive Singular Value Decomposition is one numerical method used for the extraction of peak characteristics. Simple tools have been developed to select among spectral characteristics, to reduce multiplets to single peaks, and to incorporate pre-existing chemical information into the analysis. Characteristics of this approach of parametric estimation permit somewhat different approaches to experimental design. This may be particularly valuable in the determination of multiple vicinal coupling constants about single bonds.
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Cowburn, D., Glushka, J., DiGennaro, F., Rios, C.B. (1991). Parametric Estimation in 1-D, 2-D, and 3-D NMR. In: Hoch, J.C., Poulsen, F.M., Redfield, C. (eds) Computational Aspects of the Study of Biological Macromolecules by Nuclear Magnetic Resonance Spectroscopy. NATO ASI Series, vol 225. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-9794-7_2
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