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Fast Padé transform in the theory of resonances: Exact solution of the harmonic inversion problem

机译:共振理论中的快速Padé变换:谐波反演问题的精确解

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We present the fast Padé transform (FPT) as a polynomial quotient for the Green or response function from signal processing, spectroscopy and resonant scattering theory. Specific illustrations are given for nuclear magnetic resonance spectroscopy within the problem of harmonic inversion, quantification or spectral analysis. Here, the input time signal points or auto-correlation functions are given via measurements or computations, and the task is to reconstruct the unknown components as the harmonic variables in terms of the fundamental complex frequencies and amplitudes. The FPT solves the harmonic inverse problem exactly by retrieving the true number of resonances with all their proper spectral parameters. This output list is finalized by means of Froissart doublets or pole-zero confluences for unequivocal disentangling of the physical/genuine from unphysical/spurious contents of the analysed time signal. Stability of investigated systems under external perturbations is especially challenged by the presence of noise. The FPT can assess the system's stability through determining the locations and distributions of spectral poles and zeros in the complex frequency plane. This permits identification of the regions that are void of noise, and gives the possibility for improved system performance under more stable conditions with full signal-noise separation. The FPT can provide a number of important biophysical and chemical quantities, including the density of states and abundance or concentrations of all the physical constituents from the investigated substance.
机译:我们将快速Padé变换(FPT)表示为Green的多项式商或信号处理,光谱和共振散射理论的响应函数。在谐波反转,量化或频谱分析的问题中,给出了核磁共振波谱的具体说明。在此,输入时间信号点或自相关函数是通过测量或计算给出的,任务是根据基本复频和幅度将未知分量重构为谐波变量。 FPT通过使用所有适当的频谱参数来检索共振的真实数量,从而精确地解决了谐波逆问题。该输出列表通过Froissart双重峰或零极点合流最终确定,以使物理/真正与所分析的时间信号的非物理/虚假内容明确区分。被研究系统在外部扰动下的稳定性尤其受到噪声的影响。 FPT可以通过确定复杂频率平面中频谱极点和零点的位置和分布来评估系统的稳定性。这样可以识别出没有噪声的区域,并有可能在更稳定的条件下通过完全的信噪分离来改善系统性能。 FPT可以提供许多重要的生物物理和化学量,包括状态密度以及所研究物质中所有物理成分的丰度或浓度。

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