Complexity Reduction And Regularization Of A Fast Affine Projection Algorithm For Oversampled Subband Adaptive Filters

The Affine Projection Algorithm (APA) has been shown to improve the performance of Over-Sampled Subband Adaptive Filters (OS-SAFs) compared to classical Normalized Least Mean Square (NLMS) algorithms. Because of the complexity of APA, however, only low-order APAs are practical for real-time implementation. Thus, in this paper, we propose a reduced-complexity version of the Gauss-Seidel Fast APA (GSFAPA) for adapting the subband filters in OS-SAF systems. We propose modifying the GSFAPA with a complexity reduction method based on partial filter update, and also with a low-cost method for combined regularization and step size control. We show the advantage of the new algorithm -- termed Low-Cost Gauss-Seidel Fast Affine Projection -- compared to the APA in a subband echo canceller application