Rational Fitting of S-Parameter Frequency Samples With Maximum Absolute Error Control

Rational fitting techniques are often used for the macromodeling of linear systems from tabulated S-parameter frequency samples. This letter proposes a modified weighting scheme for the Vector Fitting algorithm that iteratively minimizes the maximum absolute error over the frequency range of interest, rather than the least-squares error. By considering the appropriate error measure in the fitting process, it is possible to obtain more accurate broadband macromodels without increasing the number of poles. The effectiveness of the approach is illustrated by several numerical examples.