Rank-selection criterion for Krylov-subspace-based adaptive filtering techniques

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1 Citation (Scopus)

Abstract

We propose a novel rank-selection criterion for the Krylov-subspace-based filtering techniques such as the well-known multistage Wiener filter. We provide two necessary and sufficient conditions for the low-dimensional Krylov subspace to contain the optimal filter. The first condition is that the subspace is invariant under the transformation by the autocorrelation matrix associated with the subspace itself, and the second condition is its reverse inclusion. We derive two criteria based on the conditions; the criterion based on the first condition coincides with the conventional one, and the one based on the second is the proposed one. Simulation results indicate that the proposed criterion induces a natural relation between the threshold parameter and the average rank.

Original languageEnglish
Title of host publicationICICS 2011 - 8th International Conference on Information, Communications and Signal Processing
DOIs
Publication statusPublished - 2011 Dec 1
Event8th International Conference on Information, Communications and Signal Processing, ICICS 2011 - Singapore, Singapore
Duration: 2011 Dec 132011 Dec 16

Publication series

NameICICS 2011 - 8th International Conference on Information, Communications and Signal Processing

Other

Other8th International Conference on Information, Communications and Signal Processing, ICICS 2011
CountrySingapore
CitySingapore
Period11/12/1311/12/16

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

Cite this

Yukawa, M. (2011). Rank-selection criterion for Krylov-subspace-based adaptive filtering techniques. In ICICS 2011 - 8th International Conference on Information, Communications and Signal Processing [6174217] (ICICS 2011 - 8th International Conference on Information, Communications and Signal Processing). https://doi.org/10.1109/ICICS.2011.6174217