Ambiguity resolution in sparse linear prediction

Author

Ge, Hongya ; Tufts, Donald W. ; Kumaresan, R.

Author_Institution

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

fYear

1993

fDate

1-3 Nov 1993

Firstpage

1162

Abstract

We present some results of our analysis of Kumaresan´s (1982) sparse linear prediction method for estimation of frequencies of sinusoids. Refinements of Kumaresan´s method are proposed for the case of two sinusoids which are not close in frequency. When the data is corrupted by additive white Gaussian noise, the probability of correctly resolving ambiguities is used to evaluate the performance. Comparisons between statistical performance analyses and computer simulations demonstrate that the analyses are accurate

Keywords

filtering and prediction theory; linear systems; parameter estimation; random noise; signal processing; white noise; Kumaresan method; additive white Gaussian noise; computer simulations; frequency estimation; sinusoids; sparse linear prediction; statistical performance analyses; Additive white noise; Computer simulation; Delay estimation; Equations; Frequency estimation; Performance analysis; Polynomials; Prediction methods; Probability; Pulse measurements; Sparse matrices; Yield estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 1993. 1993 Conference Record of The Twenty-Seventh Asilomar Conference on

Conference_Location

Pacific Grove, CA

ISSN

1058-6393

Print_ISBN

0-8186-4120-7

Type

conf

DOI

10.1109/ACSSC.1993.342389

Filename

342389