We present a model-based method for estimation of relaxation parameters from time-domain NMR data specifically suitable for processing data in popular 2D phase-sensitive experiments. Our model is formulated in terms of commutative bicomplex algebra, which allows us to use the complete information available in an NMR signal acquired with principles of quadrature detection without disregarding any of its dimensions. Compared to the traditional intensity-analysis method, our model-based approach offers an important advantage for the analysis of overlapping peaks and is robust over a wide range of signal-to-noise ratios. We assess its performance with simulated experiments and then apply it for determination of [Formula: see text], [Formula: see text], and [Formula: see text] relaxation rates in datasets of a protein with more than 100 cross peaks.

中文翻译：

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多维NMR实验中的时域信号建模，用于估计弛豫参数。

我们提出了一种基于模型的方法，用于从时域NMR数据估算弛豫参数，该方法特别适合处理流行的2D相敏实验中的数据。我们的模型是用可交换双复数代数来表示的，它使我们能够使用通过正交检测原理获取的NMR信号中提供的完整信息，而无需考虑其任何维度。与传统的强度分析方法相比，我们的基于模型的方法为重叠峰的分析提供了重要的优势，并且在各种信噪比范围内都非常可靠。我们通过模拟实验评估其性能，然后将其用于确定具有超过100个交叉峰的蛋白质数据集中的[公式：参见文本]，[公式：参见文本]和[公式：参见文本]弛豫率。