Title :
Reduced-rank adaptive filtering
Author :
Goldstein, J.Scott ; Reed, Irving S.
Author_Institution :
USAF Rome Lab., NY,, USA
fDate :
2/1/1997 12:00:00 AM
Abstract :
A novel rank reduction scheme is introduced for adaptive filtering problems. This rank reduction method uses a cross-spectral metric to select the optimal lower dimensional subspace for reduced-rank adaptive filtering as a function of the basis vectors of the full-rank space
Keywords :
adaptive filters; adaptive signal processing; array signal processing; eigenvalues and eigenfunctions; filtering theory; least squares approximations; adaptive filtering; adaptive signal processing; array processing; basis vectors; cross-spectral metric; full-rank space; optimal lower dimensional subspace; rank reduction scheme; sensor array; Adaptive filters; Adaptive signal processing; Estimation theory; Laboratories; Least squares methods; Noise reduction; Parameter estimation; Steady-state; Subspace constraints; Vectors;
Journal_Title :
Signal Processing, IEEE Transactions on
