Adaptive identification of bilinear systems

Author

Zhu, Zhiwen ; Leung, Henry

Author_Institution

Commun. Res. Lab., McMaster Univ., Hamilton, Ont., Canada

Volume

3

fYear

1999

fDate

15-19 Mar 1999

Firstpage

1289

Abstract

The paper considers the adaptive identification of bilinear systems using the equation-error approach. An improved least squares (ILS) objective function is presented to reduce the bias of coefficient estimation in the case of large measurement noise when the standard least squares (LS) technique is used. An adaptive algorithm based on the ILS criterion is proposed for the identification of the bilinear system. Numerical simulations are given to demonstrate the effectiveness of the adaptive ILS algorithm. Compared with the least mean square (LMS) technique, the proposed algorithm has superior identification performance

Keywords

adaptive estimation; adaptive signal processing; bilinear systems; identification; least squares approximations; noise; ILS objective function; adaptive identification; bilinear systems; coefficient estimation; equation-error approach; improved least squares objective function; least squares technique; measurement noise; Adaptive algorithm; Least squares approximation; Least squares methods; Linear systems; Noise measurement; Noise reduction; Nonlinear equations; Nonlinear systems; Signal processing; Signal processing algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on

Conference_Location

Phoenix, AZ

ISSN

1520-6149

Print_ISBN

0-7803-5041-3

Type

conf

DOI

10.1109/ICASSP.1999.756215

Filename

756215