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声反馈抑制需求鲁棒、高效的自适应滤波器。该文提出一种基于Gauss-Seidel伪放射投影(Gauss-Seidel pseudo affine projection,GSPAP)的子带自适应声反馈消除算法。通过加权重叠相加滤波器组进行子带划分,子带上采用参考信号的自相关矩阵取代能量对滤波器的自适应步长进行归一化;在自相关矩阵的迭代公式中引入基于输入信号和参考信号能量最大值的自整定系数,增强算法鲁棒性;选用二阶GSPAP迭代法对自相关矩阵解算求逆,以平衡算法性能与复杂度。实验结果表明:在相同滤波器长度的条件下,该文方法获得11~22dB的稳态增益增量,比时域归一化最小均方误差(normalized least mean square,NLMS)方法提升20%~55%。
Acoustic feedback suppression requires a robust and efficient adaptive filter. This paper proposes a subband adaptive acoustic feedback cancellation algorithm based on Gauss-Seidel pseudo-projection (GSPAP). Sub-band partitioning is performed by weighted overlap and add-on filter bank, the self-correlation matrix of the reference signal is used in the sub-band to replace the energy to normalize the adaptive steps of the filter, and an adaptive iterative formula based on the input signal And the maximum self-tuning coefficient of reference signal energy to enhance the robustness of the algorithm. The second-order GSPAP iterative method is used to invert the autocorrelation matrix solution to balance the performance and complexity of the algorithm. The experimental results show that the steady-state gain gain of 11 ~ 22dB is achieved with the same filter length, which is 20% higher than the normalized least mean square error (NLMS) 55%.