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Sliding window adaptive SVD algorithms

Abstract : The singular value decomposition (SVD) is an important tool for subspace estimation. In adaptive signal processing, we are especially interested in tracking the SVD of a recursively updated data matrix. This paper introduces a new tracking technique, designed for rectangular sliding window data matrices. This approach, derived from the classical bi-orthogonal iteration SVD algorithm, shows excellent performance in the context of frequency estimation. It proves to be very robust to abrupt signal changes, due to the use of a sliding window. Finally, an ultra-fast tracking algorithm with comparable performance is proposed.
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Contributor : Roland Badeau Connect in order to contact the contributor
Submitted on : Monday, March 24, 2014 - 4:11:21 PM
Last modification on : Wednesday, October 14, 2020 - 1:11:49 PM
Long-term archiving on: : Tuesday, June 24, 2014 - 10:41:56 AM


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  • HAL Id : hal-00945196, version 1



Roland Badeau, Gael Richard, Bertrand David. Sliding window adaptive SVD algorithms. IEEE_J_SP, IEEE, 2004, 52 (1), pp.1--10. ⟨hal-00945196⟩



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