Acoustical feedback in hearing instruments is an annoying problem. Among the feedback reduction approaches, adaptive feedback cancellation algorithms seem to be the most promising methods. In this paper, we describe a digital hearing instrument system configuration as a standard configuration for developing adaptive feedback cancellation algorithms and evaluating their performance. We creatively divide the system into several sub-blocks and apply system identification method systematically to each sub-block. The model of each sub-block can be combined to form a complete model. We validate our model experimentally and apply our model to predict maximum stable gain and oscillation frequency, which are the most important performance parameters related to feedback cancellation algorithms.
['Jingbo Yang']
Modeling a Digital Hearing Instrument for Developing and Evaluating Adaptive Feedback Cancellation Algorithms