Pole selection of Kautz functions for system identification

A linear time-invariant model can be described either by a parametric model or by a nonparametric model. Nonparametric models, for which a priori information is not necessary, are basically the response of the dynamical system such as impulse response model and frequency models. Parametric models, such as transfer function models, can be easily described by a small number of. In this paper aiming to take benefit from both types of models, we will use linear-combination of basis functions in an impulse response using a few parameters. We will expand and generalize the Kautz functions as basis functions for dynamical system representations and we will consider estimation problem of transfer functions using Kautz function. And so we will present the influences of poles settings of Kautz function on the identification accuracy.