Chien, Ying RenYing RenChienChen, Chang CyuanChang CyuanChenHEN-WAI TSAO2023-06-192023-06-192022-01-019781665470506https://scholars.lib.ntu.edu.tw/handle/123456789/632871This paper presents a fuzzy-based approach to determine a threshold during the data selection process systematically. This makes the conventional data-selective affine projection algorithm (DSAP) robust to the impulse noise. In addition, an error-weighting vector is proposed to enhance our algorithm's robustness further. Simulation results confirmed that our proposed method ultimately improves stability, tracking ability, and robustness while reducing the weight-updating rate in the case of impulse noise presented.affine projection algorithm (APA) | data selective | fuzzy | impulse noiseconference paper10.1109/ICCE-Taiwan55306.2022.98691672-s2.0-85138754228https://api.elsevier.com/content/abstract/scopus_id/85138754228