论文标题

通过使用频率来转换,通过使用频率来降低​​1H-NMR光谱的复杂性

Reduction in the complexity of 1D 1H-NMR spectra by the use of Frequency to Information Transformation

论文作者

Valafar, Homayoun, Valafar, Faramarz

论文摘要

在收集这些光谱期间发生的巨大变化通常会阻碍1H-NMR光谱的分析。其中一些变化之一是大溶剂和标准峰,基线漂移和负峰(由于阶段不当)。此外,某些仪器依赖性变化(例如不正确的光滑)也嵌入了记录的频谱中。这些信号变化的不可预测的性质使这些光谱的自动化和仪器独立的计算机分析不可靠。在本文中,提出了一种提取信号的信息含量的新方法(在本文中,频率域1H-NMR频谱),称为频率变换转换(fit),并将其与先前使用的方法(SPUTNIK)进行了比较。 FIT可以成功将相关信息提取到信号中存在的模式匹配任务中,同时通过将傅立叶转换信号转换为信息频谱(IS)来丢弃信号的其余部分。该技术表现出降低阶层间相关系数的能力,同时增加了类内相关系数。换句话说,同一分子的不同光谱将彼此更相似,而不同分子的光谱看起来彼此更加不同。此功能可以根据计算机算法更容易地基于其光谱标记对分子进行自动识别和分析。

Analysis of 1H-NMR spectra is often hindered by large variations that occur during the collection of these spectra. Large solvent and standard peaks, base line drift and negative peaks (due to improper phasing) are among some of these variations. Furthermore, some instrument dependent alterations, such as incorrect shimming, are also embedded in the recorded spectrum. The unpredictable nature of these alterations of the signal has rendered the automated and instrument independent computer analysis of these spectra unreliable. In this paper, a novel method of extracting the information content of a signal (in this paper, frequency domain 1H-NMR spectrum), called the frequency-information transformation (FIT), is presented and compared to a previously used method (SPUTNIK). FIT can successfully extract the relevant information to a pattern matching task present in a signal, while discarding the remainder of a signal by transforming a Fourier transformed signal into an information spectrum (IS). This technique exhibits the ability of decreasing the inter-class correlation coefficients while increasing the intra-class correlation coefficients. Different spectra of the same molecule, in other words, will resemble more to each other while the spectra of different molecules will look more different from each other. This feature allows easier automated identification and analysis of molecules based on their spectral signatures using computer algorithms.

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