Fast algorithm for broadband macromodeling of high-order frequency responses

Abstract

The calculation of broadband macromodels from large tabulated frequency responses can be computationally demanding in terms of CPU time and memory, especially in the case of high-order frequency responses. To reduce the computational burden, a fast macromodeling technique is proposed. It applies a piecewise fitting strategy that makes use of a fast rational interpolation scheme to identify a representative set of data samples and an appropriate model order. This information is exploited by the Vector Fitting algorithm to extract the poles of the macromodel in a reduced amount of time. The calculation of the residues is solved as a linear approximation problem, and standard model reduction techniques can be applied as an optional step to remove possible pole redundancies. A cable case example shows that substantial savings are obtained in terms of computation time and memory requirements.