Chromatographic Data Systems: A Critical Review

Papas, Andrew N.

doi:10.1080/10408348908050072

Cited by 22 publications

(4 citation statements)

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“…The procedure has been tested on simulated data. The results are compared to a theoretical reference, not to existing methods such as non-linear regression [ 21, Kalman fltering [ 3,4], deconvolution [ 51 or integration [ 6,7].…”

Section: Introductionmentioning

confidence: 99%

Quantification of overlapping chromatographic peaks using a matched filter

Bogaert

Boelens

Smit

1994

Chemometrics and Intelligent Laboratory Systems

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A novel approach to the quantification of overlapping chromatographic peaks is introduced. The sum of the models for the individual overlapping peaks is taken as the signal model in a matched filter. Thus, the signal intensities being the objective of the quantification procedure become parameters in an overall signal model. These and, if necessary, other parameters are adapted by a modified simplex algorithm optimizing the maximum in the output of the matched filter. A prediction of the results can be made on the basis of a noiseless response surface that can be calculated from the models. When shapes and positions of the peaks are known and only their intensities need to be estimated, a quantitative theoretical error estimation is possible. The results thus predicted are considered optimal and are used as a reference in the evaluation of the results of a range of experiments using simulated data containing two overlapping Gaussians and first-order band-limited noise. The proposed procedure works well, the quality of the results usually being on or just little below the theoretical optimum. Under conditions of high overlap or a low signal to noise ratio, the experimental results no longer follow a normal distribution and their quality is lower.

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