Sliding window adaptive SVD algorithms

  title={Sliding window adaptive SVD algorithms},
  author={Roland Badeau and Ga{\"e}l Richard and Bertrand David},
  journal={IEEE Transactions on Signal Processing},
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 that is designed for rectangular sliding window data matrices. This approach, which is derived from the classical bi-orthogonal iteration SVD algorithm, shows excellent performance in the context of frequency estimation. It proves to be very robust… CONTINUE READING
Highly Cited
This paper has 53 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 33 extracted citations

53 Citations

Citations per Year
Semantic Scholar estimates that this publication has 53 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 37 references

A signal subspace approach to multiple emit t r location and spectral estimation

  • R. O. Schmidt
  • Ph.D. dissertation, Stanford Uni vers ty, Nov…
  • 1981
Highly Influential
4 Excerpts

Similar Papers

Loading similar papers…