Abstract
We introduce the Vector Fitting algorithm for the creation of reduced order models from the sampled response of a linear time-invariant system. This datadriven approach to reduction is particularly useful when the system under modeling is known only through experimental measurements. The theory behind Vector Fitting is presented for single- and multiple-input systems, together with numerical details, pseudo-codes, and an open-source implementation [75]. We discuss how the reduced model can be made stable and converted to a variety of forms for use in virtually any modeling context. Finally, we survey recent extensions of the Vector Fitting algorithm geared towards time domain, parametric and distributed systems modeling.
