Generalized fast convolution implementations of adaptive filters

Author

Petraglia, Mariane R. ; Mitra, Sanjit K.

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA

fYear

1991

fDate

11-14 Jun 1991

Firstpage

2916

Abstract

The generalized frequency domain adaptive filtering (GFDAF) algorithms are efficient implementations of the block least mean square (LMS) algorithm when small block sizes, compared to the number of adaptive coefficients, are required. The behavior of these algorithms is investigated and an examination is made of the use of a self-orthogonalization procedure and of an unconstrained form of the algorithm. Computer simulations are presented verifying the behavior of these methods, and comparing their performance to that of the subband filtering method for the acoustic echo cancelling application

Keywords

adaptive filters; digital filters; echo suppression; filtering and prediction theory; acoustic echo cancelling application; adaptive filters; block least mean square; generalized fast convolution implementation; generalized frequency domain adaptive filtering; self-orthogonalization procedure; small block sizes; subband filtering method; Acoustic applications; Adaptive filters; Application software; Computer simulation; Convolution; Filter bank; Filtering algorithms; Finite impulse response filter; Frequency domain analysis; Least squares approximation;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1991., IEEE International Sympoisum on

Print_ISBN

0-7803-0050-5

Type

conf

DOI

10.1109/ISCAS.1991.176155

Filename

176155