Relax-based estimation of Voigt lineshapes

Stefan Ingi Adalbjornsson, A. Jakobsson
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引用次数: 2

Abstract

Most spectroscopic signals are well described as having either a Lorentzian or Gaussian lineshape, and the recent literature contains a variety of estimation approaches for such models. However, several experimental works indicate that such signals can be better described as having the more general Voigt lineshape, formed as the combination of the two. Due to the inherent complexity of this model, there exist few techniques to form estimates of the parameters of the Voigt model, with a numerical search of the multidimensional nonlinear least squares (LS) cost function being the typical solution. In this paper, we propose a parametric relax-based estimator that estimates the lineshape parameters recursively, one spectral line at a time. Numerical simulations using both simulated and real measurement data illustrate the performance gain of the proposed methods.
基于松弛的Voigt线形状估计
大多数光谱信号被很好地描述为具有洛伦兹或高斯线形,并且最近的文献包含了各种用于此类模型的估计方法。然而,一些实验工作表明,这样的信号可以更好地描述为具有更一般的Voigt线形状,作为两者的结合而形成。由于该模型固有的复杂性,目前形成Voigt模型参数估计的技术很少,典型的解决方案是对多维非线性最小二乘(LS)代价函数进行数值搜索。在本文中,我们提出了一种基于参数松弛的估计器,它递归地估计线形参数,每次估计一条谱线。利用模拟和实际测量数据进行的数值模拟表明了所提出方法的性能增益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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