Creator:

Mzyk, Grzegorz

Contributor:

Korbicz, Józef (1951- ) - red.

Title:

Generalized kernel regression estimate for the identification of Hammerstein systems

Group publication title:

AMCS, volume 17 (2007)

Subject and Keywords:

Hammerstein systems ; nonparametric regression ; kernel estimation

Abstract:

A modified version of the classical kernel nonparametric identification algorithm for nonlinearity recovering in a Hammerstein system under the existence of random noise is proposed. The assumptions imposed on the unknown characteristic are weak. The generalized kernel method proposed in the paper provides more accurate results in comparison with the classical kernel nonparametric estimate, regardless of the number of measurements. The convergence in probability of the proposed estimate to the unknown characteristic is proved and the question of the convergence rate is discussed. Illustrative simulation examples are included.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2007

Resource Type:

artykuł

DOI:

10.2478/v10006-007-0018-z

Pages:

189-197

Source:

AMCS, volume 17, number 2 (2007) ; click here to follow the link

Language:

eng

License CC BY 4.0:

click here to follow the link

Rights:

Biblioteka Uniwersytetu Zielonogórskiego