An efficient stabilized fast Newton adaptive filtering algorithm for stereophonic acoustic echo cancellation SAEC

Authors:
Mohamed Djendi
Affiliations:
University Saad Dahleb of Blida, Signal Processing and Image Laboratory (LATSI), Route de Soumaa, B.P. 270, Blida 09000, Algeria
Venue:
Computers and Electrical Engineering
Year:
2012

Citing 10
Cited 1

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Adaptive filter theory (3rd ed.)
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A Better Understanding and an Improved Solution to the Problems of Stereophonic Acoustic Echo Cancellation

ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1 - Volume 1
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Improvement of the convergence speed and the tracking ability of the fast Newton type adaptive filtering (FNTF) algorithm

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Low complexity LMS-type adaptive algorithm with selective coefficient update for stereophonic acoustic echo cancellation

Computers and Electrical Engineering
An improved new error estimation algorithm for optimal filter lengths for stereophonic acoustic echo cancellation

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Numerically stable fast transversal filters for recursive leastsquares adaptive filtering

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The fast Newton transversal filter: an efficient scheme foracoustic echo cancellation in mobile radio

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Fast Newton transversal filters-a new class of adaptive estimationalgorithms

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Performance analysis of under-modelling stereophonic acoustic echo cancellation by adaptive filtering LMS algorithm

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Abstract

This paper addresses the field of stereophonic acoustic echo cancellation (SAEC) by adaptive filtering algorithms. Recently, we have proposed a new version of the fast Newton transversal FNTF algorithm for SAEC applications. In this paper, we propose an efficient modification of this algorithm for the same applications. This new algorithm uses a new proposed and simplified numerical stabilization technique and takes into account the cross-correlation between the inputs of the channels. The basic idea is to introduce a small nonlinearity into each channel that has the effect of reducing the inter-channel coherence while not being noticeable for speech due to self masking. The complexity of the proposed algorithm does not alter the complexity of the original version and is kept less than half the complexity of the fastest two-channel FTF filter version. Simulation results and comparisons with the extended two-channel normalized least mean square NLMS and FTF algorithms are presented.