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3-D AR Model Order Selection via Rank Test Procedure

Brahim Aksasse Youssef Stitou 1 Yannick Berthoumieu Mohamed Najim 1
1 IMS - Laboratoire de l'intégration, du matériau au système
Abstract : This paper deals with the problem of three dimensional AutoRegressive (3-D AR) model order estimation. We show that the information for the 3-D AR model order is implicitly contained in an appropriate matrix rank built from the AutoCorrelation Function (ACF) of the underlying 3-D Gaussian process. Exploiting this property, we develop an algorithm to estimate the order corresponding to the Quarter-Space (QS) region of support. The proposed method is based upon a Rank Test Procedure (RTP) using Singular Value Decomposition (SVD) and solving nonlinear system equations. Numerical simulations are presented to illustrate the performances of the proposed algorithm.
Keywords : three-dimensional AutoRegressive modeling Information Criteria Order Selection Quarter Space support Singular Value Decomposition three-dimensional AutoRegressive modeling.
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Journal articles
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https://hal.archives-ouvertes.fr/hal-00183339
Contributor : Yannick Berthoumieu <>
Submitted on : Monday, October 29, 2007 - 5:32:36 PM
Last modification on : Wednesday, January 31, 2018 - 1:46:02 PM

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CNRS | IMS-BORDEAUX | IMS-BORDEAUX-FUSION

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Brahim Aksasse, Youssef Stitou, Yannick Berthoumieu, Mohamed Najim. 3-D AR Model Order Selection via Rank Test Procedure. IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, 2007, 54 (7), pp.2672- 2677. ⟨10.1109/TSP.2006.874815⟩. ⟨hal-00183339⟩

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