Wavelet transform for the evaluation of peak intensities in flow-injection analysis

The application of the wavelet transform in the determination of peak intensities in flow-injection analysis was studied with regard to its properties of minimizing the effects of noise and baseline drift. The results indicate that for white noise and a favourable peak shape a signal-to-noise ratio of 2 can be tolerated at the 5% error level, which means that a significant reduction in the detection limit can be obtained in comparison with the classical signal-processing methods. With regard to the influence of a changing baseline it was found that its d.c. level has a negligible effect, but a linear or exponentially rising baseline introduces an error that depends on the chosen frequency of the wavelet that is used to determine the peak intensity. The optimum choice of this frequency, in turn, depends on the shape of the peak that is studied. In this respect significant differences were observed for pure Gaussian and exponentially modified Gaussian peaks.