Multidimensional Multiple-Order Complex Parametric Model Identification

This paper presents a way to access both the multiple-order and parameters of a multidimensional complex number autoregressive (AR) model through matrix factorization. The principle of this technique consists of the transformation of the multidimensional model to a pseudo simple-input simple-output...

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Bibliographic Details
Published in:IEEE transactions on signal processing 2008-10, Vol.56 (10), p.4574-4582
Main Authors: Kouame, D., Girault, J.-M.
Format: Article
Language:English
Subjects:
Additive noise
Algorithms
Applied sciences
Autoregressive
Complex numbers
Computer simulation
Covariance matrix
Detection, estimation, filtering, equalization, prediction
Engineering Sciences
Exact sciences and technology
Factorization
Image processing
Information, signal and communications theory
Mathematical models
Miscellaneous
multidimensional
Multidimensional systems
Neodymium
order
parameter
Parameter estimation
Parametric statistics
Recursive
Recursive estimation
Signal and communications theory
Signal and Image processing
Signal processing
Signal, noise
Spectral analysis
Telecommunications and information theory
Transformations
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Summary:This paper presents a way to access both the multiple-order and parameters of a multidimensional complex number autoregressive (AR) model through matrix factorization. The principle of this technique consists of the transformation of the multidimensional model to a pseudo simple-input simple-output AR model, then performing factorization of the covariance matrix of the data. This factorization then leads to a recursive form of the parameter and order estimation. This paper makes two principal contributions. The first is a generalization of one dimensional factored form algorithm, and the second is that it makes it possible to access all the possible different orders and parameters of a multidimensional complex number AR model of any dimension, whereas classical approaches are limited to at most four-dimensional models. Computer simulation results are provided to illustrate the behavior of this method.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2008.928088