提出一种新算法，让回声消除更快更省算力。
A Regularized Block Diagonal RLS Algorithm for Acoustic Echo Cancellation
- 用分块对角结构简化矩阵运算，实现并行处理
- 计算量大幅降低，收敛速度仍保持良好
- 适合嵌入式设备等资源受限场景使用
递归最小二乘（RLS）算法因收敛速度快，广泛应用于回声消除等自适应滤波任务，但其高计算复杂度严重限制了长滤波器的实际部署。本文提出一种正则化分块对角递归最小二乘（RBD-RLS）算法，通过将逆协方差矩阵近似为分块对角结构，将更新过程分解为独立的子块并行计算，有效降低计算复杂度。同时，对每个子块引入Tikhonov正则化以增强数值稳定性。实验结果表明，RBD-RLS在保持良好收敛性能的同时显著降低计算开销，并在真实场景中仍具备较强鲁棒性。
原文摘要 · Abstract (English)
While the recursive least square (RLS) algorithm is widely used in adaptive filtering applications like acoustic echo cancellation (AEC) due to its fast convergence rate, its high computational complexity severely limit its practical deployment for long filters. In this paper, a regularized block-diagonal RLS (RBD-RLS) algorithm is proposed to address these challenges. By approximating the inverse covariance matrix as a block-diagonal structure, RBD-RLS simplifies the update process into independent parallel computations of sub-blocks, effectively reducing the computational complexity. Additionally, Tikhonov regularization is applied to each sub-blocks for enhance numerical stability. A series of experimental results demonstrate that RBD-RLS maintains good convergence while significantly reducing computational complexity. Moreover, it still exhibits relative robustness in real-world scenarios.
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