A new evolving-update-based feedback cancellation scheme for hearing aids

Abstract

This paper proposes an efficient adaptive feedback canceller (AFC) for hearing aid, which provides satisfactory performance both in sparse and in dispersive conditions as well as can adapt according to the variations in the sparseness level of the feedback path for coloured signal as input. This is achieved by incorporating the measure of sparseness intensity and the variable step size to the memory-improved proportionate affine projection algorithm (MIPAPA), and hence, an improved MIPAPA (IMIPAPA) is proposed. Further, in order to reduce the computations incurred by the AFC, an evolving-update IMIPAPA (E-IMIPAPA) is introduced, employing an intermittent update of taps of the adaptive filter by simultaneously adjusting the update interval. The proposed E-IMIPAPA is applied to the two-microphone-based AFC. The results of simulation-based experiments show the effectiveness of the proposed algorithm as compared to the existing methods for feedback cancellation in hearing aid in terms of misalignment and added stable gain. The proposed AFC model is further extended to the multiple-microphone and single-speaker set-up.

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