摘要

Adaptive filters such as the normalized least mean square algorithm are popularly used to deal with acoustic feedback problem in hearing aids. This algorithm has to compromise between fast convergence and low misalignment. In order to meet these conflictions, a method for control of adaptation rate in acoustic feedback cancellation systems is proposed. The adaptation rate is controlled by the update state of the filter. Different adaptation rates are employed in different update states which are classified into convergent state, transitional state and steady state. The performance of the proposed method is compared with the fixed step size Normalized Least Mean Square (NLMS), Variable Step Size Normalized Least Mean Square (VSS-NLMS) based on recursive error energy and VSS-NLMS based on estimated variances. Experimental results indicate that the proposed method has better performance than other algorithms in terms of spectral distortion, Perceptual Evaluation of Speech Quality (PESQ) and average misalignment in steady state.

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