Fast Convergence Algorithm for Adaptive Noise Cancellers with SNR-Based Stepsize Control

This paper proposes a fast convergence algorithm for adaptive noise cancellers with SNR-based stepsize control. SNR-based stepsize control reduces interference by the noise-cancelled signal in adaptation. A second SNR estimate initially controls the stepsize, followed by a first SNR estimate to promote coefficient growth. The numerator of the second SNR estimate is the noise-cancelled signal obtained as the subtraction result different from the primary signal in the conventional algorithm to accelerate initial convergence. Evaluations with clean speech and noise recorded at a busy station demonstrate that the time until SNR-estimate switchover is reduced by 91% compared to the conventional algorithm, leading to fast evolution of adaptive filter coefficients.