针对自适应滤波算法中稳态失调量和收敛速度之间的矛盾,提出了一种新的变步长归一化子带自适应滤波算法.该算法在系统噪声抵消原理的基础上,用迭代收缩的方法估计得到无噪先验子带误差的功率,对每个子带步长进行更新.对所提出的算法进行数学分析,可以得出该算法是稳定的和收敛的.在长回声路径和短回声路径两种情况下,将该算法应用于助听器声反馈抑制系统中.相对于其他归一化子带自适应滤波算法,仿真实验表明,所提算法实现了更快的收敛速度,获得了更低的失调量.%A new variable step size normalized subband adaptive filtering algorithm is proposed to resolve the conflict between steady-state misalignment and convergence rate in adaptive filter algorithms. Based on the principle of cancellation of system noise,the algorithm estimates the power of the noise-free subband priori error by using the shrinkage denoising method, and updates each sub-band step size. Through mathematical analysis of the proposed algorithm,it can be concluded that the algorithm is stable and convergent. In the case of long echo path and short echo path,the algorithm is applied to the hearing aid acoustic feedback cancellation system. Compared with other normalized sub-band adaptive filter algorithms,the simulation results illustrate that the proposed algorithm achieves faster convergence rate and obtains lower misalignment.
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