<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>A new algorithm for nonparametric wavelet estimation of Hammerstein system nonlinearity is proposed. The algorithm works in the on-line regime (viz., past measurements are not available) and offers a convenient uniform routine for nonlinearity estimation at an arbitrary point and at any moment of the identification process. The pointwise convergence of the estimate to locally bounded nonlinearities and the rate of this convergence are both established.</p></abstract>

A new algorithm for nonparametric wavelet estimation of Hammerstein system nonlinearity is proposed. The algorithm works in the on-line regime (viz., past measurements are not available) and offers a convenient uniform routine for nonlinearity estimation at an arbitrary point and at any moment of the identification process. The pointwise convergence of the estimate to locally bounded nonlinearities and the rate of this convergence are both established.

On-line wavelet estimation of Hammerstein system nonlinearity

Institute of Computer Engineering, Control and Robotics Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland

International Journal of Applied Mathematics and Computer Science

{"article-title":"On-line wavelet estimation of Hammerstein system nonlinearity"}

A new algorithm for nonparametric wavelet estimation of Hammerstein system nonlinearity is proposed. The algorithm works in the on-line regime (viz., past...

On-line wavelet estimation of Hammerstein system nonlinearity

Online veröffentlicht: 27. Sept. 2010

Seitenbereich: 513 - 523

DOI: https://doi.org/10.2478/v10006-010-0038-y

Schlüsselwörter
Hammerstein systems, on-line nonparametric identification, wavelet estimates, convergence analysis

This content is open access.

On-line wavelet estimation of Hammerstein system nonlinearity

Online veröffentlicht: 27. Sept. 2010

Seitenbereich: 513 - 523

DOI: https://doi.org/10.2478/v10006-010-0038-y

SchlüsselwörterHammerstein systems, on-line nonparametric identification, wavelet estimates, convergence analysis

This content is open access.

Schlüsselwörter
Hammerstein systems, on-line nonparametric identification, wavelet estimates, convergence analysis