Parametric CARMA model identification based on WTLMS algorithm

Author

Nan-nan, Zhao ; Xin-yu, Ouyang

Author_Institution

Sch. of Electron. & Inf. Eng., Liaoning Univ. of Sci. & Technol., Anshan, China

fYear

2009

fDate

17-19 June 2009

Firstpage

1169

Lastpage

1172

Abstract

The wavelet transform domain least mean square (WTLMS) is known to have, in general, a fast convergence rate than the LMS algorithm. However, the previous papers used to identify the parameters of the CMA model with the WTLMS algorithm. In this work, a method of parametric CARMA model identification based on WTLMS algorithm is proposed, and its convergence analyses is also given. The proposed method realizes the parametric identification of CARMA model and improves greatly the precision of identification. The simulation results show the effectiveness of the proposed method.

Keywords

convergence of numerical methods; identification; least mean squares methods; wavelet transforms; convergence analysis; parametric CARMA model identification; wavelet transform domain least mean square; Algorithm design and analysis; Control systems; Convergence; Electronic mail; Finite impulse response filter; Least squares approximation; System identification; Wavelet domain; Wavelet transforms; LMS algorithm; WTLMS algorithm; system identification; wavelet transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference, 2009. CCDC '09. Chinese

Conference_Location

Guilin

Print_ISBN

978-1-4244-2722-2

Electronic_ISBN

978-1-4244-2723-9

Type

conf

DOI

10.1109/CCDC.2009.5192022

Filename

5192022