ADAPTIVE SIGNAL-SUBSPACE ALGORITHMS FOR FREQUENCY ESTIMATION AND TRACKING.

J. F. Yang; M. Kaveh

ADAPTIVE SIGNAL-SUBSPACE ALGORITHMS FOR FREQUENCY ESTIMATION AND TRACKING.

J. F. Yang, M. Kaveh

Institute of Computer and Communication Engineering

Research output: Contribution to journal › Conference article › peer-review

3 Citations (Scopus)

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
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

Fingerprint Dive into the research topics of 'ADAPTIVE SIGNAL-SUBSPACE ALGORITHMS FOR FREQUENCY ESTIMATION AND TRACKING.'. Together they form a unique fingerprint.

Cite this

@article{d643a359417c4dfb877e3bd760ca85ad,

title = "ADAPTIVE SIGNAL-SUBSPACE ALGORITHMS FOR FREQUENCY ESTIMATION AND TRACKING.",

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.",

author = "Yang, {J. F.} and M. Kaveh",

year = "1987",

month = jan,

day = "1",

language = "English",

pages = "1593--1596",

journal = "Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing",

issn = "0736-7791",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - ADAPTIVE SIGNAL-SUBSPACE ALGORITHMS FOR FREQUENCY ESTIMATION AND TRACKING.

AU - Yang, J. F.

AU - Kaveh, M.

PY - 1987/1/1

Y1 - 1987/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0023244496&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0023244496&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0023244496

SP - 1593

EP - 1596

JO - Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing

JF - Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing

SN - 0736-7791

ER -

ADAPTIVE SIGNAL-SUBSPACE ALGORITHMS FOR FREQUENCY ESTIMATION AND TRACKING.

Abstract

All Science Journal Classification (ASJC) codes

Other files and links

Cite this