应用于助听器反馈抑制系统的变步长归一化子带自适应滤波算法
Variable step size normalized sub-band adaptive filter algorithm for acoustic feedback cancellation in hearing aids

为减小自适应滤波算法中较快的收敛速度与较低的失调量之间的矛盾,提出了一种变步长归一化子带自适应滤波(VSS-NSAF)算法,并将其用于助听器声反馈抑制系统.该算法基于滤波器系数短时平均和长时平均之间的归一化距离,将滤波器的更新状态分为收敛状态、过渡状态和平稳状态.滤波器可在不同更新状态下自适应地使用不同步长,收敛状态下使用大步长以保证快速收敛,过渡状态下则使用逐步减小的阶梯状步长以进一步降低失调量,平稳状态下使用小步长以保证系统收敛至稳态解.仿真实验结果表明,与传统的归一化最小均方误差(NLMS)算法及其他子带自适应滤波算法相比,所提算法的收敛速度更快,平均稳态失调量更低.
A variable step size normalized sub-band adaptive filter(VSS-NSAF)algorithm for acoustic feedback cancellation in hearing aids is proposed to alleviate the confliction between the fast convergence rate and the low misalignment in adaptive filter algorithms. In this algorithm, the normalized distance between the short term average and the long term average of the filter coefficients is utilized to classify the filter updating states as convergent state, transitional state and steady state. Different step sizes are employed adaptively in different updating states. A large step size is adopted in the convergent state to ensure fast convergence. In the transitional state, a declining lady-like step size is employed to further lower misalignment. In order to make sure the system can finally converge, a small step size is used in steady state. The simulation results illustrate that compared with the traditional normalized least mean square(NLMS)algorithm and other sub-band adaptive filter algorithms, the proposed algorithm has the faster convergence rate and lower average steady misalignment