Minimum Eigenvalue Based 3-D AR Model Order Selection

This paper deals with the problem of three-dimensional autoregressive (3-D AR) model order estimation. Especially, we develop a practical algorithm to estimate the 3-D AR order (P1,P2,P3) corresponding to the quarter-space (QS) region of support. The proposed method is derived from the minimum descr...

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Bibliographic Details
Main Authors: Aksasse, B., Stitou, Y., Berthoumieu, Y., Najim, M.
Format: Conference Proceeding
Language:English
Subjects:
Covariance matrix
Difference equations
Eigenvalues and eigenfunctions
Gaussian processes
Multidimensional systems
Numerical simulation
Parameter estimation
Signal analysis
Singular value decomposition
White noise
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Summary:This paper deals with the problem of three-dimensional autoregressive (3-D AR) model order estimation. Especially, we develop a practical algorithm to estimate the 3-D AR order (P1,P2,P3) corresponding to the quarter-space (QS) region of support. The proposed method is derived from the minimum description length (MDL) criterion and uses the minimum eigenvalue of the covariance matrix of the underlying 3-D Gaussian process. Numerical simulations are presented to illustrate the performances of the new proposed algorithm and compare it with a recently developed method
ISSN:2373-0803
2693-3551
DOI:10.1109/SSP.2005.1628634