<abstract xmlns="http://www.w3.org/1999/xhtml"><p> A simple semi-recursive routine for nonlinearity recovery in Hammerstein systems is proposed. The identification scheme is based on the Haar wavelet kernel and possesses a simple and compact form. The convergence of the algorithm is established and the asymptotic rate of convergence (independent of the input density smoothness) is shown for piecewise- Lipschitz nonlinearities. The numerical stability of the algorithm is verified. Simulation experiments for a small and moderate number of input-output data are presented and discussed to illustrate the applicability of the routine.</p></abstract>

A simple semi-recursive routine for nonlinearity recovery in Hammerstein systems is proposed. The identification scheme is based on the Haar wavelet kernel and possesses a simple and compact form. The convergence of the algorithm is established and the asymptotic rate of convergence (independent of the input density smoothness) is shown for piecewise- Lipschitz nonlinearities. The numerical stability of the algorithm is verified. Simulation experiments for a small and moderate number of input-output data are presented and discussed to illustrate the applicability of the routine.

A simple scheme for semi-recursive identification of Hammerstein system nonlinearity by Haar wavelets

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

International Journal of Applied Mathematics and Computer Science

A simple semi-recursive routine for nonlinearity recovery in Hammerstein systems is proposed. The identification scheme is based on the Haar wavelet kernel and...

A simple scheme for semi-recursive identification of Hammerstein system nonlinearity by Haar wavelets

Online veröffentlicht: 30. Sept. 2013

Seitenbereich: 507 - 520

DOI: https://doi.org/10.2478/amcs-2013-0039

This content is open access.