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 oversampled 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, 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.

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