DocumentCode
329390
Title
Acoustic echo cancellation based on a recurrent neural network and a fast affine projection algorithm
Author
Ben Rabaa, Abdellatif ; Tourki, Rached
Author_Institution
Electron. & Micro-Electron. Lab., Sci. Fac. of Monastir, Tunisia
Volume
3
fYear
1998
fDate
31 Aug-4 Sep 1998
Firstpage
1754
Abstract
To perform real time nonlinear adaptive filtering, we propose in this paper a structure based on a recurrent neural network in cascade with a fast affine projection (FAP) algorithm. The FAP algorithm allows a large set of tradeoffs between convergence rate, residual error, tracking capacity, and arithmetic complexity. Hence, the proposed structure has the potential for solving difficult nonlinear adaptive signal processing tasks; such as system identification where nonlinearity and nonstationarity are both important factors. The adaptive signal processing capability of the proposed structure has been tested in the context of the acoustic echo cancellation
Keywords
acoustic signal processing; adaptive filters; echo; echo suppression; filtering theory; nonlinear filters; recurrent neural nets; acoustic echo cancellation; arithmetic complexity; convergence rate; fast affine projection algorithm; nonlinear adaptive signal processing; nonlinearity; nonstationarity; real time nonlinear adaptive filtering; recurrent neural network; residual error; system identification; tracking capacity; Adaptive filters; Adaptive signal processing; Arithmetic; Convergence; Echo cancellers; Filtering algorithms; Financial advantage program; Recurrent neural networks; Signal processing algorithms; System identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics Society, 1998. IECON '98. Proceedings of the 24th Annual Conference of the IEEE
Conference_Location
Aachen
Print_ISBN
0-7803-4503-7
Type
conf
DOI
10.1109/IECON.1998.722948
Filename
722948
Link To Document