Fast algorithm for broadband macromodeling of high-order frequency responses

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.