Map model order selection rule for 2-D sinusoids in white noise

Mark A. Kliger, Joseph M. Francos

Research output: Contribution to conferencePaperpeer-review

Abstract

We consider the problem of jointly estimating the number as well as the parameters of two-dimensional sinusoidal signals, observed in the presence of an additive white Gaussian noise field. Existing solutions to this problem are based on model order selection rules, derived for the parallel one-dimensional problem. These criteria are then adapted to the two-dimensional problem using heuristic arguments. Employing asymptotic considerations, we derive in this paper a maximum a-posteriori (MAP) model order selection criterion for jointly estimating the parameters of the two-dimensional sinusoids and their number.

Original languageEnglish
Pages118-122
Number of pages5
StatePublished - 1 Jan 2000
EventProceedings of the 10th IEEE Workshop on Statiscal and Array Processing - Pennsylvania, PA, USA
Duration: 14 Aug 200016 Aug 2000

Conference

ConferenceProceedings of the 10th IEEE Workshop on Statiscal and Array Processing
CityPennsylvania, PA, USA
Period14/08/0016/08/00

Fingerprint

Dive into the research topics of 'Map model order selection rule for 2-D sinusoids in white noise'. Together they form a unique fingerprint.

Cite this