Abstract
Continuous wavelet transform (CWT) is a new powerful tool for removing noise, irrelevant information and signal baseline correction of voltammograms. In this application, morlet continuous wavelet transforms (ML-CWT) for signal treatments were found to be suitable among the wavelet families. MLCWT approach was applied to the peak current data vectors consisting of 139 data points in the potential range of (−1004) – (−1556) mV versus Ag/AgCl reference electrode. Peak current data for the calibration and prediction steps in the concentration range of 83.0–375.0 µg=mL zafirlukast were obtained by using Osteryoung Square Wave Adsorption Stripping Voltammetry (OSWAdSV).
Three different calibration models namely mean centering calibration (MCC), principal component regression (PCR) and partial least squares (PLS) were constructed by using the relationship between concentration set and CWT-coefficients of the peak current data. The proposed methods were validated by analyzing the synthetic samples and standard addition samples. These methods were successfully applied to the quantitative analysis of zafirlukast in tablets and satisfactory results were reported.
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Süslü, İ., Dinç, E., Altinöz, S. (2007). An application of continuous wavelet transform to electrochemical signals for the quantitative analysis. In: Taş, K., Tenreiro Machado, J.A., Baleanu, D. (eds) Mathematical Methods in Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-5678-9_26
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DOI: https://doi.org/10.1007/978-1-4020-5678-9_26
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