Two-dimensional subband Steiglitz-McBride algorithm for automatic analysis of two-dimensional nuclear magnetic resonance data
© 2019 John Wiley & Sons, Ltd.
| Veröffentlicht in: | Magnetic resonance in chemistry : MRC. - 1985. - 58(2020), 1 vom: 07. Jan., Seite 106-115 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2020
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| Zugriff auf das übergeordnete Werk: | Magnetic resonance in chemistry : MRC |
| Schlagworte: | Journal Article 2D Steiglitz-McBride 2D-BIC 2D-IPF 2D-NMR algorithm automatic subband |
| Zusammenfassung: | © 2019 John Wiley & Sons, Ltd. Rapid, accurate, and automatic quantitation of two-dimensional nuclear magnetic resonance(2D-NMR) data is a challenging problem. Recently, a Bayesian information criterion based subband Steiglitz-McBride algorithm has been shown to exhibit superior performance on all three fronts when applied to the quantitation of one-dimensional NMR free induction decay data. In this paper, we demonstrate that the 2D Steiglitz-McBride algorithm, in conjunction with 2D subband decomposition and the 2D Bayesian information criterion, also achieves excellent results for 2D-NMR data in terms of speed, accuracy, and automation-especially when compared in these respects to the previously published analysis techniques for 2D-NMR data |
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| Beschreibung: | Date Completed 27.01.2020 Date Revised 27.01.2020 published: Print Citation Status PubMed-not-MEDLINE |
| ISSN: | 1097-458X |
| DOI: | 10.1002/mrc.4960 |