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Is independent component analysis appropriate for multivariate resolution in analytical chemistry?

机译:独立成分分析是否适合分析化学中的多元分辨率?

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In this article, we examine Independent Component Analysis (ICA) and the concept of Mutual information (MI) as a quantitative measure of independence from the point of view of analytical chemistry. We compare results obtained by different ICA methods with results obtained by Multivariate Curve Resolution Alternating Least Squares (MCR-ALS). These results have shown that, when non-negativity constraints are applied, values of MI increase considerably and the resolved components cannot anymore be considered to be independent (i.e. they can only be considered to be the " least dependent" components). MI values of profiles resolved by MCR-ALS and ICA did not differ significantly when non-negativity constraints were applied. In addition, since data-fitting values were also practically the same in both cases, the solutions provided by them should be considered equivalent from a mathematical point of view and within the region of feasible solutions for the particular set of applied constraints. We therefore conclude that the solutions based only on the independence concept are not necessarily better from the point of view of analytical chemistry than those obtained by other proposed MCR methods. Results obtained in this work also show that ICA can be considered an alternative tool for resolving mixed signals only in a limited number of cases.
机译:在本文中,我们将从分析化学的角度研究独立成分分析(ICA)和互信息(MI)的概念,作为对独立性的定量度量。我们将通过不同ICA方法获得的结果与通过多元曲线分辨率交替最小二乘(MCR-ALS)获得的结果进行比较。这些结果表明,当应用非负约束时,MI的值显着增加,并且分辨出的分量不再被认为是独立的(即,它们只能被认为是“依赖性最小”的分量)。当应用非负约束时,MCR-ALS和ICA解析的配置文件的MI值没有显着差异。另外,由于两种情况下的数据拟合值实际上也是相同的,因此从数学的角度以及对于特定的应用约束集,在可行解的范围内,应将它们提供的解决方案视为等效。因此,我们得出结论,从分析化学的角度来看,仅基于独立性概念的解决方案不一定比其他提议的MCR方法获得的解决方案更好。从这项工作中获得的结果还表明,仅在少数情况下,ICA可以被视为解决混合信号的替代工具。

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