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多重重建熵最小化方法:从混合光谱中对纯组分进行无监督光谱重建,无需使用先验信息。

The multi-reconstruction entropy minimization method: unsupervised spectral reconstruction of pure components from mixture spectra, without the use of a priori information.

作者信息

Zhang Huajun, Chew Wee, Garland Marc

机构信息

Institute of Chemical and Engineering Science, 1 Pesek Road, Jurong Island, Singapore 627833.

出版信息

Appl Spectrosc. 2007 Dec;61(12):1366-72. doi: 10.1366/000370207783292172.

DOI:10.1366/000370207783292172
PMID:18198030
Abstract

The band-target entropy minimization method (BTEM) and its variant methods excel at reconstructing known/unknown pure spectra from mixtures without prior information. These mixtures may represent either non-reactive or even reactive systems. In this work, an unsupervised form of the entropy minimization curve resolution, namely, the multi-reconstruction entropy minimization method (MREM), is presented. MREM differs from BTEM by removing the need for band-targets and by introducing a multiple search routine to find multiple local entropy minima. This multiple search routine, which provides a rapid survey of spectral estimates, utilizes a localized form of Corona's simulated annealing method in the optimization. The objective functions and penalty functions of the BTEM type methods are essentially retained. Compared to BTEM type methods, MREM (1) searches for multiple local minima instead of a single global minimum and hence reconstructs many pure component spectra at once instead of one pure spectrum; and (2) utilizes a user-defined broad spectral range [v1, v2] for all searches instead of multiple user-defined narrow "targets" as in BTEM. The new MREM has been tested on four sets of real spectra using Fourier transform infrared spectroscopy (FT-IR), mass spectroscopy (MS), and ultraviolet-visible (UV-Vis) spectroscopy. The results show that MREM is computationally much faster than BTEM for finding the major components present. Also, because MREM does not rely on band targeting, it is very useful for spectra that have no localized features and are highly overlapping, such as UV-Vis.

摘要

波段目标熵最小化方法(BTEM)及其变体方法擅长在无先验信息的情况下从混合物中重建已知/未知纯光谱。这些混合物可能代表非反应性甚至反应性系统。在这项工作中,提出了一种无监督形式的熵最小化曲线分辨方法,即多重重建熵最小化方法(MREM)。MREM与BTEM的不同之处在于,它无需波段目标,并引入了多重搜索程序来寻找多个局部熵最小值。这种多重搜索程序在优化过程中利用了Corona模拟退火方法的局部形式,能快速全面地评估光谱估计值。BTEM类方法的目标函数和惩罚函数基本得以保留。与BTEM类方法相比,MREM:(1)搜索多个局部最小值而非单个全局最小值,因此能一次性重建多个纯组分光谱而非一个纯光谱;(2)在所有搜索中使用用户定义的宽光谱范围[v1, v2],而非像BTEM那样使用多个用户定义的窄“目标”。新的MREM已通过傅里叶变换红外光谱(FT-IR)、质谱(MS)和紫外可见光谱(UV-Vis)对四组真实光谱进行了测试。结果表明,在寻找存在的主要成分方面,MREM在计算速度上比BTEM快得多。此外,由于MREM不依赖波段目标,对于没有局部特征且高度重叠的光谱(如UV-Vis光谱)非常有用。

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