A rank test based approach to order estimation. I. 2-D AR models application

In system identification and parametric spectral estimation by two-dimensional (2-D) autoregressive (AR) and 2-D autoregressive moving average (ARMA) models, the order selection problem is often required. In this correspondence, we show that the information of 2-D AR model order is implicitly contai...

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Veröffentlicht in:IEEE transactions on signal processing 1999-07, Vol.47 (7), p.2069-2072
Hauptverfasser: Aksasse, B., Badidi, L., Radouane, L.
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Badidi, L.
Radouane, L.
description In system identification and parametric spectral estimation by two-dimensional (2-D) autoregressive (AR) and 2-D autoregressive moving average (ARMA) models, the order selection problem is often required. In this correspondence, we show that the information of 2-D AR model order is implicitly contained in a correlation matrix. An algorithm for 2-D quarter-plane AR model order determination is proposed. Numerical simulations are presented to show the efficiency of the proposed singular value decomposition (SVD) based algorithm.
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subjects Autoregressive processes
Image storage
Matrix decomposition
Parameter estimation
Quadratic programming
Radar signal processing
Signal processing algorithms
System identification
Testing
Two dimensional displays
title A rank test based approach to order estimation. I. 2-D AR models application
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