Abstract: The wavelet transform converts the information contained in the analytical signal into a two-dimensional time - frequency form. A coefficient is chosen that gives the peak intensity optimally filtered from noise. The choice of this coefficient is made automatically from its max. value observed in a well defined peak at a high concentration. The theory of the transform and equations for its practical application are given. The performance was tested on flow injection analysis of two systems, injection of imidazole into a reagent stream of 0.2 M acetic acid and injection of 18-crown-6 into a 0.2 M BaCl2 reagent stream, with enthalpimetric detection. The method was useful in minimizing the effect of 'white' noise and, to a lesser extent, of baseline drift. The detection limits by the wavelet transform were lower for imidazole and 18-crown-6 than with use of the peak height method; peak area gave much poorer sensitivity. 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 favorable peak shape a sigESIK:o-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 DC 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.

Abstract: The use of solid-phase reactors in flow-through analytical systems was recently discussed (Nondek et al., Ibid., 1983, 55, 1466). It is shown that a reaction chromatogram of a fast and irreversible first-order reaction in such a reactor can be approximated by use of the exponentially modified Gaussian function. The described approach makes it possible to separate the Gaussian component of band broadening from the reaction broadening characterized by the time constant. Consequently, the performance of HPLC or flow injection analysis derivatization reactors packed with a solid catalyst or reagent can be discussed more exactly, e.g., in terms of relative plate loss or relative system efficiency.

Abstract: A method is described for the generation of an acceptable approximation of exponentially modified functions representing parameter changes vs. time. Exponentially modified Gaussian functions give an ideal peak shape model, but not for tailing peaks. Flow injection analysis peaks are more accurately described by exponentially modified square functions.

Abstract: A review with 127 references. Of the exponentially modified Gaussian (EMG) function as model for real chromatography peaks. This review covers the following areas: (1) equations derived from the EMG model, (2) studies of inherent errors in the quantitation of chromatography peaks via use of the EMG model, (3) chromatography applications since 1983, and (4) applications to flow injection anal.