Steady-state analysis of continuous adaptation in acoustic feedback reduction systems for hearing-aids

Abstract

Acoustic feedback is a problem in hearing aids that contain a substantial amount of gain, hearing aids that are used in conjunction with vented or open molds, and in-the-ear hearing aids. Acoustic feedback is both annoying and reduces the maximum usable gain of hearing-aid devices. This paper studies analytically the steady-state convergence behavior of LMS-based adaptive algorithms when used in continuous adaptation to reduce acoustic feedback. A bias is found in the adaptive filter's estimate of the hearing-aid acoustic feedback path. Methods for reducing this bias and producing an improved estimate of the acoustic feedback path are analyzed and compared. It is shown that by the use of a delay in the forward or cancellation paths of the hearing aid plant, and for representative feedback paths, it is possible to reduce this bias by more than 15 dB.