A low rank weighted matrix approximation method for robust estimation of sinusoid parameters

Author

Edelson, Geoffrey S. ; Kumaresan, Ramdas ; Tufts, Donald W.

Author_Institution

Dept. of Electr. Eng., Rhode Island Univ., Kingston, RI, USA

Volume

5

fYear

1992

fDate

23-26 Mar 1992

Firstpage

533

Abstract

Techniques based on linear prediction (LP) and the singular value decomposition (SVD) for the robust estimation of the parameters of closely spaced exponentially damped sinusoidal signals in additive noise are extended and improved. An iterative method of fitting lower-rank least squares approximations subject to a general choice of weights is used. The method is applied to data sequences consisting of one and two signals with impulsive noise or with missing data samples

Keywords

approximation theory; filtering and prediction theory; matrix algebra; parameter estimation; signal processing; SVD; additive noise; closely spaced signals; data samples; data sequences; exponentially damped sinusoidal signals; impulsive noise; iterative method; least squares approximations; linear prediction; low rank method; singular value decomposition; sinusoid parameter estimation; weighted matrix approximation; Additive noise; Additive white noise; Approximation methods; Contracts; Filters; Iterative methods; Least squares approximation; Noise robustness; PSNR; Parameter estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on

Conference_Location

San Francisco, CA

ISSN

1520-6149

Print_ISBN

0-7803-0532-9

Type

conf

DOI

10.1109/ICASSP.1992.226565

Filename

226565