THREE-DIMENSIONAL AUTOREGRESSIVE PARAMETER ESTIMATION FROM NOISY DATA (TueAmPO2)
Author(s) :
Youssef Stitou (LAPS - Univesité Bordeaux1, France)
Marc Donias (LAPS - ENSEIRB, France)
Brahim Aksasse (Departement informatique - FTS - Errachidia, Morocco)
Abstract : This paper deals with the three-dimensional Autoregressive (3-D AR) model parameter estimation from noisy data. We develop an algorithm to estimate the transversal AR parameters corresponding to the Quarter-Space (QS) region of support without a priori knowledge of additive noise power. The transversal parameters and the noise variance are both obtained as a solution of a quadratic eigenvalue problem. The performance of the proposed algorithm is evaluated by numerical examples.
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