Abstract
An adaptive estimator, and its practical implementations, of the complete noise- or signal-subspace of a sample covariance matrix are presented. The general formulation of the proposed estimator results from an asymptotic argument which shows the signal- or noise-subspace computation to be equivalent to a constrained gradient search procedure. Two categories of unbiased estimators of the gradient, possessing varying degrees of complexity, are presented and the convergence rates of these estimates are discussed.
Original language | English |
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Pages (from-to) | 1593-1596 |
Number of pages | 4 |
Journal | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
Publication status | Published - 1987 Jan 1 |
All Science Journal Classification (ASJC) codes
- Software
- Signal Processing
- Electrical and Electronic Engineering