Adaptive filter theory (2nd ed.)
Adaptive filter theory (2nd ed.)
Combined acoustic echo control and noise reduction for hands-free telephony
Signal Processing - Special issue on acoustic echo and noise control
Adaptation of a memoryless preprocessor for nonlinear acoustic echo cancelling
Signal Processing - Special issue on current topics in adaptive filtering for hands-free acoustic communication and beyond
Acoustic Echo and Noise Control: A Practical Approach
Acoustic Echo and Noise Control: A Practical Approach
Nonlinear acoustic echo cancellation with 2nd order adaptive Volterra filters
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Adaptive Nonlinearity Identification in a Hammerstein System using a Pseudo Coherence Function
SSP '07 Proceedings of the 2007 IEEE/SP 14th Workshop on Statistical Signal Processing
Partitioned block frequency-domain adaptive second-order Volterra filter
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Stochastic mean-square performance analysis of an adaptive Hammerstein filter
IEEE Transactions on Signal Processing - Part I
A stable adaptive Hammerstein filter employing partial orthogonalization of the input signals
IEEE Transactions on Signal Processing
Identification of certain time-varying nonlinear Wiener andHammerstein systems
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Information Theory
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Acoustic echo is an annoying issue for many hands-free telecommunication systems. Because of room acoustics and delay in the transmission path, echoes affect the sound quality and may hamper communications. Thus, acoustic echo cancellers (AECs) are critical for enhancing the audio quality. Echo cancellation is challenging because long room impulse response slows down the convergence rate and increases the computational complexity of the AEC designs. Nonlinearity of the power amplifier or the loudspeaker further exacerbates the problem. In this paper, we propose a novel AEC algorithm when the loudspeaker-enclosure-microphone system is described by a Hammerstein model. We show that by introducing a channel shortening filter, the length of the ''effective'' acoustic echo path is reduced considerably. Hence, the computational complexity of AECs is reduced and the convergence rate is increased. Adaptive algorithms are developed for the proposed structure and their convergence is shown analytically. The effectiveness of our method is illustrated by computer simulations.