In this letter, an effective acoustic feedback cancellation algorithm is proposed based on the normalized sub-band adaptive filter (NSAF). To improve the confliction between fast convergence rate and low misalignment in the NSAF algorithm, a variable step size is designed to automatically vary according to the update state of the filter. The update state of the filter is adaptively detected via the normalized distance between the long term average and the short term average of the tap-weight vector. Simulation results demonstrate that the proposed algorithm has superior performance in terms of convergence rate and misalignment.

Acoustic feedback is a major complaint of hearing aid users. Adaptive filters are a common method for suppressing acoustic feedback in digital hearing aids. In this letter, we propose a new variable step-size algorithm for normalized least mean square and an affine projection algorithm to combine with a variable step-size affine projection algorithm and global speech absence probability in an adaptive filter. The computer simulation used to test the proposed algorithm results in a lower misalignment error than the comparison algorithm at a similar convergence rate. Therefore, the proposed algorithm suggests an effective solution for the feedback suppression system of digital hearing aids.

The application of an active noise control system in a finite-length duct is studied. Previously proposed single-input-single-output systems are inappropriate in this case, because reflection at the terminals degrades the performance, and/or infinite-impulse-response filters are required for perfect noise cancellation. In this paper, we propose a single-input-single-output system applicable to finite-length ducts, which theoretically achieves perfect noise cancellation while using finite-impulse-response filters only. The tap lengths of the filters are as short as the delays between the reference sensor and the secondary source. A useful implementation of the proposed system is also discussed.