Linear parametric models for signals with long-range dependence and infinite variance

Author

Kogon, Siephen M. ; Manolakis, Dimifris G.

Author_Institution

Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA

Volume

3

fYear

1995

fDate

9-12 May 1995

Firstpage

1597

Abstract

Two models of long-range dependence with finite and infinite variance that have been proposed in the mathematics literature are considered. The models are used for the characterization of experimental data in order to determine the possible benefits they offer over existing models. They are presented under a unified framework and their similarities and differences are investigated by applying the models to real world data in the form of infrared background signals

Keywords

autoregressive moving average processes; correlation methods; signal processing; characterization; experimental data; finite variance; infinite variance; infrared background signals; linear parametric models; long-range dependence; unified framework; Biological system modeling; Biomedical signal processing; Digital signal processing; Fractals; Gaussian distribution; Hydrology; Laboratories; Parametric statistics; Probability distribution; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on

Conference_Location

Detroit, MI

ISSN

1520-6149

Print_ISBN

0-7803-2431-5

Type

conf

DOI

10.1109/ICASSP.1995.479869

Filename

479869