An effective approach to adaptive IIR filtering

Author

Harteneck, M. ; Stewart, R.W. ; McWhirter, J.G. ; Proudler, Ian K.

Author_Institution

Dept. of Electron. & Electr. Eng., Strathclyde Univ., Glasgow, UK

Volume

3

fYear

1996

fDate

7-10 May 1996

Firstpage

1633

Abstract

An approach to adaptive IIR filtering based on a pseudo-linear regression and a QR matrix decomposition is developed. The algorithm has proved to be stable and has good convergence properties if the unknown system satisfies the strictly positive real condition. The derivation of the algorithm is straightforward and the computational complexity is less than the computational complexity of the IIR-RPE algorithm. Simulation results of system identification with synthetic and real world data are shown comparing the algorithm with the IIR-RPE and the IIR-LMS algorithm

Keywords

IIR filters; adaptive filters; adaptive signal processing; computational complexity; convergence of numerical methods; filtering theory; identification; matrix decomposition; statistical analysis; IIR-LMS algorithm; IIR-RPE algorithm; QR matrix decomposition; adaptive IIR filtering; computational complexity; convergence properties; pseudolinear regression; real world data; simulation results; strictly positive real condition; synthetic data; system identification; Adaptive filters; Adaptive signal processing; Computational complexity; Convergence; Equations; Filtering; Finite impulse response filter; IIR filters; Least squares methods; Signal processing algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on

Conference_Location

Atlanta, GA

ISSN

1520-6149

Print_ISBN

0-7803-3192-3

Type

conf

DOI

10.1109/ICASSP.1996.544117

Filename

544117