Proportionate NSAF algorithms with sparseness-measured for acoustic echo cancellation |
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Affiliation: | 1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, China;2. School of Information and Communication Engineering, Dalian University of Technology, Dalian, China;1. Federal University of Rio de Janeiro, EPOLI, COPPE, CP 68504, CEP 21945-970, Rio de Janeiro, Brazil;2. CEFET, Nova Iguaçu, and Federal University of Rio de Janeiro, COPPE, Rio de Janeiro, Brazil |
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Abstract: | In acoustic echo cancellation (AEC), the sparseness of impulse responses can vary over time or/and context. For such scenario, the proportionate normalized subband adaptive filter (PNSAF) and μ-law (MPNSAF) algorithms suffer from performance deterioration. To this end, we propose their sparseness-measured versions by incorporating the estimated sparseness into the PNSAF and MPNSAF algorithms, respectively, which can adapt to the sparseness variation of impulse responses. In addition, based on the energy conservation argument, we provide a unified formula to predict the steady-state mean-square performance of any PNSAF algorithm, which is also supported by simulations. Simulation results in AEC have shown that the proposed algorithms not only exhibit faster convergence rate than their competitors in sparse, quasi-sparse and dispersive environments, but also are robust to the variation in the sparseness of impulse responses. |
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Keywords: | Acoustic echo cancellation Proportionate normalized subband adaptive filter algorithm Sparseness-measured Sparse impulse responses Dispersive impulse responses |
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