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
fDate :
1/1/1994 12:00:00 AM
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;
Journal_Title :
Signal Processing, IEEE Transactions on
