Discrete wavelet assisted correlation optimised warping of chromatograms: optimizing the computational time for correcting the drifts in peak positions

Abstract

Correlation optimised warping (COW) has been the most favourite chromatographic peak alignment approach in recent years. After optimization of the two parameters, slack and segment length, COW works well in aligning the chromatograms. However, one of the serious disadvantages of COW is that it is computationally time consuming. Often several segment lengths and slack parameters need to be tested to find the optimum combination for achieving the alignment that makes the whole analysis take several hours. In the present work, it has been shown that with the application of wavelet analysis prior to alignment it is possible to provide the necessary computational economy to the COW algorithm.