| Title | An Improved MLMS Algorithm with Prediction Error Method for Adaptive Feedback Cancellation |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Liu, Jiawei, Liu, Quanli, Wang, Wei, Wang, Xiao- Lei |
| Conference Name | 2021 International Conference on Security, Pattern Analysis, and Cybernetics（SPAC) |
| Keywords | adaptive feedback cancellation, adaptive filtering, adaptive filters, Adaptive systems, Correlation, Estimation, Levinson-Durbin algorithm, Metrics, Modified Least Mean Square, Prediction algorithms, prediction error method, Predictive models, pubcrawl, resilience, Resiliency, Scalability, simulation, variable step-size |
| Abstract | Adaptive feedback cancellation (AFC) method is widely adopted for the purpose of reducing the adverse effects of acoustic feedback on the sound reinforcement systems. However, since the existence of forward path results in the correlation between the source signal and the feedback signal, the source signal is mistakenly considered as the feedback signal to be eliminated by adaptive filter when it is colored, which leads to a inaccurate prediction of the acoustic feedback signal. In order to solve this problem, prediction error method is introduced in this paper to remove the correlation between the source signal and the feedback signal. Aiming at the dilemma of Modified Least Mean Square (MLMS) algorithm in choosing between prediction speed and prediction accuracy, an improved MLMS algorithm with a variable step-size scheme is proposed. Simulation examples are applied to show that the proposed algorithm can obtain more accurate prediction of acoustic feedback signal in a shorter time than the MLMS algorithm. |
| DOI | 10.1109/SPAC53836.2021.9539993 |
| Citation Key | liu_improved_2021 |
An Improved MLMS Algorithm with Prediction Error Method for Adaptive Feedback Cancellation