Fast adaptive algorithms for minor component analysis using Householder transformation

S Bartelmaos, K Abed-Meraim - Digital Signal Processing, 2011 - Elsevier
In this paper, we propose new adaptive algorithms for the extraction and tracking of the least
(minor) or eventually, principal eigenvectors of a positive Hermitian covariance matrix. The
main advantage of our proposed algorithms is their low computational complexity and
numerical stability even in the minor component analysis case. The proposed algorithms are
considered fast in the sense that their computational cost is O (np) flops per iteration where n
is the size of the observation vector and p< n is the number of eigenvectors to estimate. We …
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