Adaptive feedback cancellation in hearing aids

In general feedback cancellation setups, standard adaptive filtering techniques fail to provide a reliable feedback path estimate if the desired signal is spectrally colored because of the presence of a closed signal loop. In this paper, several approaches for improving the estimation accuracy of the adaptive feedback canceller in hearing aids will be reviewed, including constrained adaptation and bandlimited adaptation of the feedback canceller as well as adaptation with the prediction-error method (PEM) using a fixed or adaptive model of the desired signal. Partitioned-block frequency-domain implementations of these algorithms will be compared for acoustic feedback paths measured in two commercial behind-the-ear hearing aids. In addition, it is shown that the tracking performance of the PEM-based feedback canceller with adaptive signal model can be improved by the so-called shadow filter approach known from echo cancellation.