Creating accurate multivariate rational interpolation models of microwave circuits by using efficient adaptive sampling to minimize the number of computational electromagnetic analyses

A fast and efficient adaptive sampling algorithm for multivariate rational interpolation models based on convergents of Thiele-type branched continued fractions (BCFs) is presented in this paper. We propose a variation of the standard BCF that uses approximation to establish a nonrectangular grid of support points. Starting with a low-order interpolant, the technique syste matically increases the order by optimally choosing new support points in t he areas of highest error until the required accuracy is achieved. In this way, accurate surrogate models are established by a small number of support points without any a priori knowledge of the data. The technique is evalua ted on several passive microwave structures.