Set-membership improved normalized subband adaptive filter algorithms for acoustic echo cancellation
For acoustic echo cancellation systems, the proposed algorithms offer improved performance and lower complexity, but the improvement is incremental over existing INSAF methods.
This paper proposes set-membership versions of improved normalized subband adaptive filter (INSAF) algorithms for acoustic echo cancellation, achieving smaller steady-state error and significantly reduced computational complexity. Smooth variants further improve steady-state performance.
In order to improve the performances of recently-presented improved normalized subband adaptive filter (INSAF) and proportionate INSAF algorithms for highly noisy system, this paper proposes their set-membership versions by exploiting the theory of set-membership filtering. Apart from obtaining smaller steady-state error, the proposed algorithms significantly reduce the overall computational complexity. In addition, to further improve the steady-state performance for the algorithms, their smooth variants are developed by using the smoothed absolute subband output errors to update the step sizes. Simulation results in the context of acoustic echo cancellation have demonstrated the superiority of the proposed algorithms.