Wavelet Analysis in Analytical Chemistry

Wavelet analysis has been proved to be a high performance signal processing technique. In this paper, with a brief introduction of the basic theory and the Mallat pyramid algorithm of the wavelet analysis, new algorithms which are more suitable for processing analytical signals were described, and the works which we have done recently were reported. The main characteristic of the wavelet transform is the dual localization property in both time domain and frequency/scale domain, which enables the wavelet analysis to decompose a signal into contributions which represent the information of different frequency contained in the original signal. Therefore, many applications based on the frequency analysis can be achieved by the technique, such as de-noising, baseline correction, and resolution of overlapping signal, etc. Another characteristic of the wavelet analysis is that it is a linear decomposition, which enables us to do quantitative determination using the decomposed contributions.