ADAPTIVE SIGNAL-SUBSPACE ALGORITHMS FOR FREQUENCY ESTIMATION AND TRACKING.

J. F. Yang, M. Kaveh

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations

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 languageEnglish (US)
Pages (from-to)1593-1596
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - Jan 1 1987

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