Equal convergence conditions for normal- and partitioned-frequency domain adaptive filters

Author

Sommen, P.C.W. ; de Wilde, E.

Author_Institution

Dept. of Electr. Eng., Eindhoven Univ. of Technol., Netherlands

Volume

4

fYear

1992

fDate

23-26 Mar 1992

Firstpage

69

Abstract

Convergence characteristics of adaptive filters are influenced by statistical properties of the input signal. In order to remove this dependency, decorrelation can be applied with a frequency- domain adaptive filter (FDAF), in which the length M of the transformation between the time and the frequency domain is chosen to be equal to the length N of the adaptive filter. The relevant length M is determined by the statistical properties of the input signal and needs not to be equal to N. Both lengths M and N can be decoupled by using partitioned frequency-domain adaptive filters (PFDAFs). Statistical conditions are derived for the input signal in such a way that both PFDAF and FDAF have equal convergence properties

Keywords

adaptive filters; convergence; correlation theory; digital filters; frequency-domain analysis; convergence; decorrelation; normal-frequency domain adaptive filters; partitioned-frequency domain adaptive filters; Adaptive filters; Approximation algorithms; Convergence; Decorrelation; Delay lines; Discrete Fourier transforms; Fourier transforms; Frequency domain analysis; Least squares approximation; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on

Conference_Location

San Francisco, CA

ISSN

1520-6149

Print_ISBN

0-7803-0532-9

Type

conf

DOI

10.1109/ICASSP.1992.226409

Filename

226409