New adaptive IIR filtering algorithms based on the Steiglitz-McBride method

Author

Cousseau, Juan E. ; Diniz, Paulo S R

Author_Institution

Dept. of Electron., Federal Univ. of Rio de Janeiro, Brazil

Volume

45

Issue

5

fYear

1997

fDate

5/1/1997 12:00:00 AM

Firstpage

1367

Lastpage

1371

Abstract

This correspondence introduces a family of algorithms based on the Steiglitz-McBride (SM) method for adaptive IIR filtering. The main feature of the proposed algorithms is to remove the parameter bias induced by colored measurement noise. The conceptual similarities between the SM method and the equation error method are explored in order to analyze some properties of the new algorithms. The main analysis results concern the consistency of the parameter estimates and local convergence. A set of simulations in a system identification configuration is included in order to verify the improved performance of the new algorithms based on the SM method

Keywords

IIR filters; adaptive filters; adaptive signal processing; convergence of numerical methods; filtering theory; parameter estimation; Steiglitz-McBride method; adaptive IIR filtering algorithms; colored measurement noise; equation error method; local convergence; parameter estimation; system identification; Adaptive filters; Algorithm design and analysis; Colored noise; Convergence; Equations; Filtering algorithms; IIR filters; Noise measurement; Parameter estimation; Samarium;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.575712

Filename

575712