The Andrew's sine function is a robust estimator, which has been used in
outlier rejection and robust statistics. However, the performance of such
estimator does not receive attention in the field of adaptive filtering
techniques. Two Andrew's sine estimator (ASE)-based robust adaptive filtering
algorithms are proposed in this brief. Specifically, to achieve improved
performance and reduced computational complexity, the iterative Wiener filter
(IWF) is an attractive choice. A novel IWF based on ASE (IWF-ASE) is proposed
for impulsive noises. To further reduce the computational complexity, the
leading dichotomous coordinate descent (DCD) algorithm is combined with the
ASE, developing DCD-ASE algorithm. Simulations on system identification
demonstrate that the proposed algorithms can achieve smaller misalignment as
compared to the conventional IWF, recursive maximum correntropy criterion
(RMCC), and DCD-RMCC algorithms in impulsive noise. Furthermore, the proposed
algorithms exhibit improved performance in partial discharge (PD) denoising.Comment: 5 pages, 5 figure