@inproceedings{838d7cc87256429296542a5aa0630ccd,
title = "Fast principal component analysis and data whitening algorithms",
abstract = "In this paper, we propose an adaptive implementation of a fast-convergent algorithm for principal component extraction. Our approach consists of first estimating a basis of the principal subspace through the use of OPAST algorithm. The obtained basis is then fed to a second process where at each iteration one or several Givens transformations are applied to estimate the principal components. Later on, the proposed PCA algorithm is used to derive a fast data whitening solution that overcomes the existing ones of similar complexity order. Simulation results support the high performance of our algorithms in terms of accuracy and speed of convergence.",
keywords = "Adaptive algorithms, Data whitening, Givens rotation, Principal Subspace tracking, Principal component analysis",
author = "Messaoud Thameri and Abla Kammoun and Karim Abed-Meraim and Adel Belouchrani",
year = "2011",
doi = "10.1109/WOSSPA.2011.5931434",
language = "English (US)",
isbn = "9781457706905",
series = "7th International Workshop on Systems, Signal Processing and their Applications, WoSSPA 2011",
pages = "139--142",
booktitle = "7th International Workshop on Systems, Signal Processing and their Applications, WoSSPA 2011",
note = "7th International Workshop on Systems, Signal Processing and their Applications, WoSSPA 2011 ; Conference date: 09-05-2011 Through 11-05-2011",
}