Please use this identifier to cite or link to this item: https://doi.org/10.1109/PIMRC.2006.254444
Title: Efficient and fast tracking algorithm for minor component analysis
Authors: Bartelmaos, S.
Abed-Meraim, K.
Attallah, S. 
Issue Date: 2006
Source: Bartelmaos, S.,Abed-Meraim, K.,Attallah, S. (2006). Efficient and fast tracking algorithm for minor component analysis. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC : -. ScholarBank@NUS Repository. https://doi.org/10.1109/PIMRC.2006.254444
Abstract: In this paper, we propose new adaptive algorithms for the extraction and tracking of the least (minor) eigenvectors of a positive Hermitian covariance matrix. The proposed algorithm is said fast in the sense that its computational cost is of order O(np) flops per iteration where n is the size of the observation vector and p < n is the number of minor eigenvectors we need to estimate. This algorithm is based on a stochastic gradient technique and a fast orthogonalization procedure that guarantees the algorithm stability and the orthogonality of the weight matrix at each iteration. Despite its low computational cost, the proposed algorithm is quite efficient as shown by simulation experiments and performs better than other existing methods of higher computational complexity. © 2006 IEEE.
Source Title: IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
URI: http://scholarbank.nus.edu.sg/handle/10635/70102
ISBN: 1424403294
DOI: 10.1109/PIMRC.2006.254444
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