Pole selection of Kautz functions for system identification

Chul Min Bae, Kiyoshi Wada, Jun Imai

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)119-123
Number of pages5
JournalResearch Reports on Information Science and Electrical Engineering of Kyushu University
Issue number2
Publication statusPublished - Sep 1 1999
Externally publishedYes

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering


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