Name
Abstract | ||
|---|---|---|
Subspace decomposition has proven to be an important tool in adaptive signal processing. A number of algorithms have been proposed for tracking the dominant subspace. Among the most robust and most efficient methods is the projection approximation and subspace tracking (PAST) method. This paper elaborates on an orthonormal version of the PAST algorithm for fast estimation and tracking of the princ... |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1109/97.823526 | IEEE Signal Processing Letters |
Keywords | DocType | Volume |
Signal processing algorithms,Covariance matrix,Convergence,Vectors,Approximation algorithms,Matrix decomposition,Principal component analysis,Adaptive signal processing,Data compression,System identification | Journal | 7 |
Issue | ISSN | Citations |
3 | 1070-9908 | 44 |
PageRank | References | Authors |
2.07 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| K. Abed-Meraim | 1 | 1962 | 164.99 |
| A. Chkeif | 2 | 84 | 6.16 |
| Y. Hua | 3 | 209 | 19.58 |