Robust Subspace Tracking with Contamination Mitigation via α-Divergence

Le Trung Thanh; Aref Miri Rekavandi; Abd-Krim Seghouane; Karim Abed-Meraim

ICASSP 2023accepted0 citations

Robust Subspace Tracking with Contamination Mitigation via α-Divergence

Le Trung Thanh, Aref Miri Rekavandi, Abd-Krim Seghouane, Karim Abed-Meraim

Abstract

We studied the problem of robust subspace tracking (RST) in contaminated environments. Leveraging the fast approximated power iteration and α-divergence, a novel robust algorithm called αFAPI was developed for tracking the underlying principal subspace of streaming data over time. αFAPI is fast and it outperforms many RST methods while only having a low complexity linear to the data dimension. Some experiments were conducted to illustrate the performance of αFAPI.

BibTeX

@inproceedings{icassp2023_robustsubspacetr,
  title = {Robust Subspace Tracking with Contamination Mitigation via α-Divergence},
  author = {Le Trung Thanh and Aref Miri Rekavandi and Abd-Krim Seghouane and Karim Abed-Meraim},
  booktitle = {ICASSP 2023},
  year = {2023}
}