A gradient-based adaptive algorithm with reduced complexity, fast convergence and good tracking characteristics

Author

Benesty, Jacob ; Wen, Li Sheng ; Duhamel, Pierre

Author_Institution

CNET, Issy-Les-Moulineaux, France

Volume

4

fYear

1992

fDate

23-26 Mar 1992

Firstpage

5

Abstract

A new block processing algorithm which requires a smaller number of arithmetic operations than the least mean square (LMS) algorithm, while converging faster is described. Theoretical conditions for this convergence to be faster are derived and checked by simulation. Some simulations are provided showing that, at least under some specific conditions, its tracking characteristics are also improved. These performances are obtained by grouping the computations corresponding to a block of successive inputs. Good performances are obtained even with very small blocks

Keywords

acoustic signal processing; adaptive filters; convergence; digital filters; echo suppression; filtering and prediction theory; acoustic echo; adaptive filters; block processing algorithm; echo cancellation; fast convergence; gradient-based adaptive algorithm; reduced complexity; simulations; tracking characteristics; Adaptive algorithm; Arithmetic; Computational modeling; Convergence; Echo cancellers; Equations; Error correction; Filters; Least squares approximation; Signal processing algorithms;

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.1992.226425

Filename

226425