Skip to Main content Skip to Navigation
Journal articles

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.
Complete list of metadata

https://hal.inria.fr/hal-00945196
Contributor : Roland Badeau <>
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

File

ieee-tsp-04.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-00945196, version 1

Collections

Citation

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

Share

Metrics

Record views

306

Files downloads

2107