通過選擇性地多相修剪來降低部分更新過采樣子頻帶自適應(yīng)算法的復

COMPLEXITY REDUCTION OF PARTIAL UPDATE OVERSAMPLED SUBBAND
ADAPTIVE ALGORITHMS BY SELECTIVE PRUNING OF POLYPHASE COMPONENTS

Partial update algorithms such as sequential LMS have been
proposed to reduce computation cost. To further decrease the
computation cost for low-resource real-time echo cancellation by
oversampled subband adaptive filters (OS-SAFs), we propose a
new hybrid partial update algorithm. This algorithm, based on a
polyphase perspective, selectively prunes (zeros out) polyphase
components of the adaptive filter. When employed on OS-SAFs,
the proposed algorithm achieves significant complexity
reduction. This algorithm is applied to sequential versions of
LMS and Pseudo-Affine Projection algorithms employed to
adapt OS-SAFs. Presented performance evaluations prove that
considerable computation cost reduction (typically more than
four times) is feasible with practically insignificant degradations
in the steady-state performance of the OS-SAF system.
Moreover, the algorithm does not affect initial convergence properties.