Multidimensional complex number parametric model order and parameters estimation

Denis Kouamé (1, 2) , Carole Garnier (2) , Jean-Marc Grégoire (3, 2) , Jean-Marc Girault (3, 2)

1 IRIT-TCI - Traitement et Compréhension d’Images
2 LUSSI - Laboratoire Ultrasons Signaux et Instrumentation
3 iBraiN - Imaging, Brain & Neuropsychiatry

This paper presents a technique for accessing multidimensional complex number AR model order and parameters through matrix factorization. The principle of this technique consists of the transformation of the multidimensional model to a pseudo SISO (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. The methodology developed here may be applied to an AR model of any dimension. Computer simulation results are provided to illustrate the behavior of this method

Mots clés: Multidimensional systems; Parametric statistics; Parameter estimation; Covariance matrix; Electronic mail; Recursive estimation; Computer simulation; Additive noise; Multidimensional signal processing; Signal processing

Domaines: Traitement du signal et de l'image [eess.SP]

Denis Kouamé, Carole Garnier, Jean-Marc Grégoire, Jean-Marc Girault. Multidimensional complex number parametric model order and parameters estimation. IEEE International Conerence on Acoustics, Speech, and Signal Processing (poster session) (ICASSP 2006), May 2006, Toulouse, France. pp.321-324, ⟨10.1109/ICASSP.2006.1660655⟩. ⟨hal-03149783⟩