Rapid frequency-domain adaptation of causal FIR filters

Author

Elliott, Stephen J. ; Rafaely, Boaz

Author_Institution

Inst. of Sound & Vibration Res., Southampton Univ., UK

Volume

4

Issue

12

fYear

1997

Firstpage

337

Lastpage

339

Abstract

Normalizing the convergence coefficient of the block frequency-domain least mean square (LMS) algorithm in each frequency bin can improve the convergence rate, but in some applications can lead to a biased steady-state solution if the filter is constrained to be strictly causal. An algorithm is presented in which the spectral factors of the bin-normalized convergence coefficient are used before and after the causality constraint is applied in the adaptation algorithm, which converges rapidly to the optimal causal filter.

Keywords

FIR filters; adaptive filters; adaptive signal processing; convergence of numerical methods; filtering theory; frequency-domain analysis; least mean squares methods; LMS algorithm; adaptation algorithm; adaptive filter; biased steady-state solution; bin-normalized convergence coefficient; block frequency-domain least mean square; causal FIR filters; causality constraint; convergence coefficient normalization; convergence rate; frequency bin; optimal causal filter; rapid frequency-domain adaptation; spectral factors; Adaptive filters; Convergence; Convolution; Discrete Fourier transforms; Filtering; Finite impulse response filter; Frequency domain analysis; Least squares approximation; Mean square error methods; Steady-state;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/97.650039

Filename

650039