Title :
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
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;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.479869
