Conjugate gradient algorithms for minor subspace analysis - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2007

Conjugate gradient algorithms for minor subspace analysis

Abstract

We introduce a conjugate gradient method for estimating and tracking the minor eigenvector of a data correlation matrix. This new algorithm is less computationally demanding and converges faster than other methods derived from the conjugate gradient approach. It can also be applied in the context of minor subspace tracking, as a pre-processing step for the YAST algorithm, in order to enhance its performance. Simulations show that the resulting algorithm converges much faster than existing minor subspace trackers.
Fichier principal
Vignette du fichier
icassp-07.pdf (215.24 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00945274 , version 1 (24-03-2014)

Identifiers

  • HAL Id : hal-00945274 , version 1

Cite

Roland Badeau, Bertrand David, Gael Richard. Conjugate gradient algorithms for minor subspace analysis. Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2007, Honolulu, Hawaii, United States. pp.1013--1016. ⟨hal-00945274⟩
53 View
119 Download

Share

Gmail Facebook X LinkedIn More