Uygun maliyetli seyrekliğe duyarlı akustik geri besleme giderici.

One of the important problems encountered in acoustic feedback canceller (AFC) systems is the AF path has a sparse nature. This situation deteriorates the convergence rate and steady-state error of AFC systems. On the other hand, large-scale source signals such as speech/music and using high filter orders increase the computational cost of AFC systems. To this end, in this study, a cost-effective l0-norm-online censoring (OC)-least mean square (LMS) (l0-OC-LMS) based AFC system (l0-OC-AFC) is proposed, which solves the sparse problem of the AF path by processing only informative data instead of all the data. Thus, the proposed AFC system significantly contributes to reducing the computational complexity without sacrificing its performance. This is achieved by combining the OC strategy and the l0penalty norm promoting sparsity. The proposed l0-OC-AFC system is comprehensively tested in terms of the misalignment (MIS) and the added stable gain (ASG) on real-world long sparse AF paths measured from a behind-the-ear hearing aid. Simulation results reveal the effectiveness of the proposed l0-OC-AFC system. [ABSTRACT FROM AUTHOR]