Title :
Improving the resolution capability of the parametric power spectrum density on the base of an additive linear prediction process
Author :
Tykhonov, V.A. ; Kudriavtseva, N.V.
Author_Institution :
Dept. of Radio-Electron. Syst., Kharkiv Nat. Univ. of Radioelectron., Kharkiv, Ukraine
Abstract :
New linear prediction polymodels is described in the article. The structure of the universal linear prediction model is shown. We propose new additive linear prediction model AR1(2)+AR2(2). We also obtain spectral characteristics of additive processes and a system of equations for calculation of the additive model´s parameters. Comparative analysis of resolution capability is made using four methods of statistical modeling.
Keywords :
autoregressive processes; spectral analysis; statistical analysis; additive linear prediction process; additive model parameter; linear prediction polymodel; parametric power spectrum density resolution capability; spectral characteristics; statistical modeling; system of equations; universal linear prediction model; Additives; Analytical models; Autoregressive processes; Computational modeling; Equations; Mathematical model; Predictive models; autoregressive linear prediction models; lattice filter; linear prediction polymodels; power spectrum density;
Conference_Titel :
Radioelektronika (RADIOELEKTRONIKA), 2013 23rd International Conference
Conference_Location :
Pardubice
Print_ISBN :
978-1-4673-5516-2
DOI :
10.1109/RadioElek.2013.6530955
