A parametric set of spectral estimates and their performance

Author

Ugrinovsky, Roman

Author_Institution

Inst. of Appl. Phys., Acad. of Sci., Nizhny Novgorod, Russia

Volume

3

fYear

1995

fDate

9-12 May 1995

Firstpage

1641

Abstract

A novel rigorous approach to the spectral density estimation problem based on the trigonometric moment problem technique is considered. Using the trigonometric moment problem results, all possible extrapolations of the autocorrelation function, which are in agreement with a set of known values are found. A-wide set of spectral estimators is described in terms of polynomials orthogonal with respect to the given autocorrelation sequence. The parametric representation for this set is given. The performance of the proposed spectral estimator with arbitrary parametrization function is established

Keywords

correlation methods; estimation theory; extrapolation; method of moments; parameter estimation; polynomials; spectral analysis; arbitrary parametrization function; autocorrelation function; autocorrelation sequence; extrapolations; moment method; parametric representation; parametric set; performance; polynomials; spectral density estimation; spectral estimates; trigonometric moment problem; Autocorrelation; Concrete; Extrapolation; Maximum likelihood estimation; Multiple signal classification; Physics; Polynomials; Sensor arrays; Signal processing; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on

Conference_Location

Detroit, MI

ISSN

1520-6149

Print_ISBN

0-7803-2431-5

Type

conf

DOI

10.1109/ICASSP.1995.479886

Filename

479886