Pure component spectral recovery and constrained matrix factorizations: concepts and applications
Pure component spectral recovery and constrained matrix factorizations: concepts and applications
复制标题
纯分量光谱恢复和约束矩阵分解：概念和应用
DOI：
10.1002/cem.1273
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发表时间：
2010
影响因子：
2.4
通讯作者：
D. Hess
中科院分区：
文献类型：
--
作者：
K. Neymeyr;M. Sawall;D. Hess
我们提出了一种自建模因子分析方法的新思想，该方法允许从一组光谱测量中提取纯组分光谱和相关的浓度分布。该方法的实用性的证明和比较与模型问题的既定工具，并为系统从催化加氢铑络合物都与重叠的组分光谱。自建模方法倾向于最大限度地减少恢复光谱的重叠，这可能导致光谱和浓度分布的不必要的失真。对于强重叠光谱，对吸收率矩阵因子的特定奇异值的惩罚条件和全局分解方法是构造改进的因子分解的适当工具。版权所有© 2010约翰威利父子有限公司.
We present new ideas underlying a self‐modelling factor analytical method which allows to extract pure component spectra and the associated concentration profiles from a set of spectroscopic measurements. The usefulness of the method is demonstrated and compared with established tools for model problems and for a system from catalytic hydroformylation by Rhodium complexes both with overlapping component spectra. Self‐modelling methods tend to minimize the overlap of the recovered spectra, which can result in an unwanted distortion of the spectra and concentration profiles. For strongly overlapping spectra a penalty condition on a specific singular value of the absorptivity matrix factor and a global decomposition approach are appropriate tools to construct improved factorizations. Copyright © 2010 John Wiley & Sons, Ltd.