Abstract:
Nonlinear acoustic echo cancellation (NAEC) aims at estimating both the acoustic impulse response and the nonlinearities affecting the desired signal. Both the modeling p...Show MoreMetadata
Abstract:
Nonlinear acoustic echo cancellation (NAEC) aims at estimating both the acoustic impulse response and the nonlinearities affecting the desired signal. Both the modeling processes show behaviors of sparse nature from an energy point of view. In this paper, we propose an adaptive NAEC algorithm that takes advantage of such sparsity behaviors to improve echo cancellation performance. The proposed scheme is characterized by two block-based adaptive combinations of proportionate adaptive filters, having different strategies, devoted respectively to the estimation of the linear and nonlinear responses. The proposed model is assessed in NAEC problems, where its advantages and effectiveness are shown.
Published in: 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)
Date of Conference: 13-16 September 2016
Date Added to IEEE Xplore: 10 November 2016
ISBN Information: