DocumentCode
1016661
Title
Efficient estimation of the signal subspace without eigendecomposition
Author
Davila, Carlos E. ; Asmoodeh, M.
Author_Institution
Dept. of Electr. Eng., Southern Methodist Univ., Dallas, TX, USA
Volume
42
Issue
1
fYear
1994
fDate
1/1/1994 12:00:00 AM
Firstpage
236
Lastpage
239
Abstract
A method of obtaining estimates of a set of basis vectors spanning the signal subspace without eigendecomposition is described. Each basis vector can be determined as the solution to a linear least-squares prediction problem, thereby offering a reduction in computation of one order of magnitude compared with eigendecomposition-based methods. Experiments suggest that the proposed method has performance equal to that of MUSIC
Keywords
filtering and prediction theory; least squares approximations; linear systems; parameter estimation; signal processing; basis vectors; computation reduction; linear least-squares prediction problem; signal subspace; Adaptive arrays; Antennas and propagation; Frequency estimation; Maximum likelihood estimation; Multiple signal classification; Signal processing; Signal processing algorithms; Signal resolution; Speech processing; Vectors;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.258149
Filename
258149
Link To Document