Abstract
A class of singular value decomposition (SVD)-type subspace trackers based on the overdetermined row-Householder principle is introduced. These algorithms are maximally fast with a dominant operations count of 3Nr multiplications per time update. They can be regarded as square-root forms of previously introduced conventional fast subspace trackers and offer interesting features such as perfectly orthonormal basis estimates, lowest dynamic range requirements, and highest numerical robustness and stability. Several variants of the method are proposed and studied experimentally.
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References
Businger P.A.: Updating a singular value decomposion, Nordisk Tidskr. Inf. Behandling (BIT) 10, 376–397 (1970)
Bunch J.R., Nielsen C.P.: Updating the singular value decomposition. Numer. Math. 31, 111–128 (1978)
Karasalo I.: Estimating the covariance matrix by signal subspace averaging. IEEE Trans. Acoust. 34, 8–12 (1986)
Dowling E.M., Ammann L.P., DeGroat R.D.: A TQR-iteration adaptive SVD for real time angle and frequency tracking. IEEE Trans. Signal Process. 42, 914–926 (1994)
Bauer F.L.: Das Verfahren der Treppeniteration und verwandte Verfahren zur Lösung algebraischer Eigenwertprobleme. Z. Angew. Math. Phys. 8, 214–235 (1957)
Golub G.H., Van Loan C.F.: Matrix Computations, 2nd edn. John Hopkins University Press, Baltimore (1989)
Strobach P.: Bi-iteration SVD subspace tracking algorithms. IEEE Trans. Signal Process. 45, 1222–1240 (1997)
Strobach P.: Square Hankel SVD subspace tracking algorithms. Signal Process. 57(1), 1–18 (1997)
Ouyang S., Hua Y.: Bi-Iterative least-square method for subspace tracking. IEEE Trans. Signal Process. 53, 2984–2996 (2005)
Badeau R., David B., Richard G.: Fast approximated power iteration subspace tracking. IEEE Trans. Signal Process. 53, 2931–2941 (2005)
Strobach P.: Low rank adaptive filters. IEEE Trans. Signal Process. 44, 2932–2947 (1996)
Strobach, P.: The fast recursive row-Householder subspace tracking algorithm. Signal Process. (2009). doi:10.1016/j.sigpro.2009.04.012
Bojanczyk A.W., Nagy J.G., Plemmons R.J.: Block RLS using row Householder reflections. Linear Algebra Appl. 188, 31–62 (1993)
Strobach P.: The fast Householder Bi-SVD subspace tracking algorithm. Signal Process. 88(8), 2651–2661 (2008)
Stange P., Griewank A., Bollhöfer M.: On the efficient update of rectangular LU-factorizations subject to low-rank modifications. Electron. Trans. Numer. Anal. 26, 161–177 (2007)
Strobach, P.: The Householder compressor theorem and its application in subspace tracking. Signal Process. (2008). doi:10.1016/j.sigpro.2008.11.001
Strobach P.: Updating the principal angle decomposition. Numer. Math. 110(1), 83–112 (2008)
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Strobach, P. Square-root Householder subspace tracking. Numer. Math. 113, 89–121 (2009). https://doi.org/10.1007/s00211-009-0229-3
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DOI: https://doi.org/10.1007/s00211-009-0229-3