A Linear Kronig‐Kramers Transform Test for Immittance Data Validation

Abstract

A method is described with which immittance data can be tested for Kronig‐Kramers compliance. In contrast with other procedures, this method is linear in nature and is based on a predetermined set of relaxation times. The model contains as many parameters (or less) as there are data sets. Three modes of operation are described, the first two are based on a linear fit of the model function to the imaginary part or to the real part of the data set. With the fit parameters the corresponding real or imaginary dispersion can be calculated and compared with the actual measurement. In the third mode a complex model function is fitted to the complete data set. As the model function does comply with (a relaxed set of) the Kronig‐Kramers (K‐K) rules, it will not be able to reproduce the data set satisfactory in the case of nonK‐K behavior, as can be observed from the residuals plot. Due to its linear nature, no starting values are needed for the data validation. The main limitation of this procedure is the size of the matrix and the accuracy of the matrix inversion.