Identification of input-output bilinear systems using cumulants

Author

Tsoulkas, Vasilis ; Koukoulas, Panos ; Kalouptsidis, Nicholas

Author_Institution

Div. of Commun. & Signal Process., Athens Univ., Greece

Volume

49

Issue

11

fYear

2001

fDate

11/1/2001 12:00:00 AM

Firstpage

2753

Lastpage

2761

Abstract

This paper is concerned with the identification of a discrete input-output bilinear system driven by an independent identically distributed (i.i.d.) stochastic input and corrupted by measurement noise. A novel algorithmic procedure for the direct computation of the unknown model parameters is developed based on crosscumulant information up to third order. Simulations and comparisons with a least squares type identification method are provided

Keywords

Volterra series; bilinear systems; higher order statistics; identification; stochastic processes; Volterra series representation; crosscumulant information; cumulants; discrete input-output bilinear system; i.i.d. stochastic input; independent identically distributed stochastic input; least squares type identification method; measurement noise; model parameters computation algorithm; parameter estimation; simulations; system identification; Additive noise; Computational modeling; Electromagnetic modeling; Kernel; Least squares methods; Noise measurement; Nonlinear equations; Nonlinear systems; Signal processing algorithms; Stochastic systems;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.960423

Filename

960423