Fractional Wavelet Analysis of the Composite Signals of Two-Component Mixture by Multivariate Spectral Calibration

Abstract

The fractional wavelet transform is a new mathematical tool for signal and image analysis. In this study, fractional wavelet analysis of the composite signals of the components in a binary mixture was investigated. In the quantitative evaluation of hydrochlorothiazide and cilazapril, partial least squares calibration was applied to the fractional wavelet coefficients after optimization of the experimental conditions. The validation of the partial least squares approach was tested by analyzing various synthetic mixtures consisting of active compounds of interest. Hydrochlorothiazide and cilazapril in real samples were analyzed using partial least squares calibration based on the fractional wavelet coefficients without a prior chemical separation procedure. This combined method is a potential new chemometric approach and is suitable for quantitative analysis of the components in samples.