Fitting MA models to linear non-Gaussian random fields using higher order cumulants

Author

Tugnait, Jitendra K.

Author_Institution

Dept. of Electr. Eng., Auburn Univ., AL, USA

Volume

45

Issue

4

fYear

1997

fDate

4/1/1997 12:00:00 AM

Firstpage

1045

Lastpage

1050

Abstract

A general (possibly nonminimum phase and/or asymmetric noncausal) two-dimensional (2-D) moving average (MA) model driven by a zero-mean i.i.d. 2-D sequence is considered. The input sequence is not observed. The signal observations may be noisy. We consider the problems of model order determination and model parameter estimation using the higher order (third- or fourth-order, for example) cumulants of the 2-D signal. Second-order statistics of the data can consistently identify only a smaller class of MA models. The proposed approaches are illustrated via computer simulations

Keywords

higher order statistics; modelling; moving average processes; parameter estimation; random processes; sequences; signal processing; 2-D signal; computer simulation; higher order cumulants; linear non-Gaussian random fields; model order determination; noisy signals; parameter estimation; signal observations; two-dimensional moving average model; zero-mean i.i.d. 2-D sequence; Computer simulation; Focusing; Higher order statistics; Image texture; Infrared imaging; Linear systems; Parameter estimation; Statistical distributions; Transfer functions; Two dimensional displays;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.564192

Filename

564192