Strongly consistent model order selection for estimating 2-D sinusoids in colored noise

Mark Kliger; Joseph M. Francos

doi:10.1109/TIT.2013.2249181

Strongly consistent model order selection for estimating 2-D sinusoids in colored noise

Mark Kliger
, Joseph M. Francos

Department of Electrical & Computer Engineering

Ben-Gurion University of the Negev

Research output: Contribution to journal › Article › peer-review

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.

Original language	American English
Article number	6471234
Pages (from-to)	4408-4422
Number of pages	15
Journal	IEEE Transactions on Information Theory
Volume	59
Issue number	7
DOIs	https://doi.org/10.1109/TIT.2013.2249181
State	Published - 15 Jul 2013

Keywords

Least squares estimation
model order selection
strong consistency
two-dimensional random fields

ASJC Scopus subject areas

Information Systems
Computer Science Applications
Library and Information Sciences

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10.1109/TIT.2013.2249181

Cite this

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title = "Strongly consistent model order selection for estimating 2-D sinusoids in colored noise",

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.",

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N2 - 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.

AB - 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.

KW - Least squares estimation

KW - model order selection

KW - strong consistency

KW - two-dimensional random fields

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DO - 10.1109/TIT.2013.2249181

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ER -

Strongly consistent model order selection for estimating 2-D sinusoids in colored noise

Abstract

Keywords

ASJC Scopus subject areas

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