Implementation of the regularization and cumulant techniques for interpreting and modeling analytical signals

A new approach to the modeling of analytical signals based on the combined Tikhonov regularization and cumulant analysis of random non-Gaussian processes, allowing us to subtract the background, determine and refine the parameters, and to separate overlapping peaks is presented. The efficiency of the developed procedure in analyzing the stripping voltammetric measurements of analytical signals for Cd(II), Cu(II), and Pb(II) pollutants of natural water at mercury-graphite electrodes is demonstrated.