DocumentCode :
2251919
Title :
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
Link To Document :
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