DocumentCode :
71664
Title :
Strongly Consistent Model Order Selection for Estimating 2-D Sinusoids in Colored Noise
Author :
Kliger, M. ; Francos, Joseph M.
Author_Institution :
Omek Interactive Ltd., Bet Shemesh, Israel
Volume :
59
Issue :
7
fYear :
2013
fDate :
Jul-13
Firstpage :
4408
Lastpage :
4422
Abstract :
The problem of jointly estimating the number as well as the parameters of 2-D sinusoidal signals, observed in the presence of an additive colored noise field, is considered. We begin by establishing the strong consistency of the nonlinear least squares estimator of the parameters of 2-D sinusoids, when the number of sinusoidal signals assumed in the field is incorrect. Based on these results, we prove the strong consistency of a new family of model order selection rules.
Keywords :
noise; signal processing; 2D sinusoidal signal; additive colored noise field; model order selection rules; nonlinear least squares estimator; Additive noise; Additives; Colored noise; Data models; Least squares approximation; Vectors; Least squares estimation; model order selection; strong consistency; two-dimensional random fields;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.2013.2249181
Filename :
6471234
Link To Document :
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