Review
Version 2
Preserved in Portico This version is not peer-reviewed
Mathematical and Statistical Review of NMR Time Domain Data Pre-Processing
Version 1
: Received: 28 October 2023 / Approved: 31 October 2023 / Online: 31 October 2023 (08:14:42 CET)
Version 2 : Received: 7 January 2024 / Approved: 8 January 2024 / Online: 8 January 2024 (14:05:37 CET)
Version 2 : Received: 7 January 2024 / Approved: 8 January 2024 / Online: 8 January 2024 (14:05:37 CET)
How to cite: Jiang, A. Mathematical and Statistical Review of NMR Time Domain Data Pre-Processing. Preprints 2023, 2023102032. https://doi.org/10.20944/preprints202310.2032.v2 Jiang, A. Mathematical and Statistical Review of NMR Time Domain Data Pre-Processing. Preprints 2023, 2023102032. https://doi.org/10.20944/preprints202310.2032.v2
Abstract
Nuclear Magnetic Resonance (NMR) and its various forms are extensively utilized in both research and clinical settings to analyse molecules. NMR data pre-processing, while essential to NMR data analysis, can be uniquely complex. Despite the availability of software tools, understanding these processes can be challenging, complicating the selection of appropriate pre-processing steps. In this review, we elucidate pre-processing steps in the time domain from a mathematical and statistical perspective, explaining direct current offset removal, eddy current correction, shift and linear prediction, weighting, zero filling, and domain transformation using plain language and fundamental mathematical formulas. Our objective is to clarify these processes in simple terms and provide general guidance.
Keywords
NMR; pre-processing; direct current offset removal; eddy current correction; weighting; domain transformation
Subject
Computer Science and Mathematics, Signal Processing
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Commenter: Aixiang Jiang
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