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Comparison of the performances of several commonly used algorithms for second-order calibration

Abstract

The present study compared six commonly used algorithms, namely, alternating trilinear decomposition (ATLD), self-weighted alternating trilinear decomposition (SWATLD), alternating coupled two unequal residual functions (ACTUF), parallel factor analysis (PARAFAC), damped Gauss-Newton (dGN) and algorithm combination methodology (ACM). Their performances on the pre-estimated component number, convergence rate, collinearity, noise, small component and slight non-linearity (chromatographic peak drift) were considered. The results indicate that the difference in the performances of the algorithms arises from differences in the computational mode and the construction of loss functions. Among the six algorithms, ATLD, SWATLD, ACTUF and ACM were insensitive to the excessive factors; the ability to overcome the severe collinearity was in the order of ACM, ACTUF and dGN > SWATLD > ATLD and PARAFAC; PARAFAC, dGN and ACM showed a stronger ability to resist the noise; PARAFAC was the most sensitive to the small component; and ATLD and SWATLD could overcome some effect of slight non-linearity (chromatographic peak drift). Additionally, ATLD was found to be the fastest algorithm, and dGN and ACM had faster convergent rates than PARAFAC. This study is helpful for understanding the essential difference in the performances of algorithms and can provide guidance for choosing suitable algorithms for the analysis of three-way data.

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Publication details

The article was received on 29 Jun 2018, accepted on 04 Sep 2018 and first published on 05 Sep 2018


Article type: Paper
DOI: 10.1039/C8AY01443D
Citation: Anal. Methods, 2018, Accepted Manuscript
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    Comparison of the performances of several commonly used algorithms for second-order calibration

    Y. Li, H. Gu, H. Wu and X. Yu, Anal. Methods, 2018, Accepted Manuscript , DOI: 10.1039/C8AY01443D

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