Detail publikace

Evaluation of methods for AR coefficients estimation using monte carlo analysis

KLEJMOVÁ, E.

Originální název

Evaluation of methods for AR coefficients estimation using monte carlo analysis

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

Aim of this paper is to give recommendation for work with methods used for estimation of coefficients of autoregressive process. We applied Monte Carlo simulations to investigate perfor-mance of Burg, Yule-Walker and covariance methods. Evaluation of precision of spectral estimation is done with focus on signal length and lag order. The results are presented in graphical form and briefly discussed. Taking these results into account, Yule-Walker method shows better performance in case of long length signals and in case of overvalued lag order. Burg and covariance methods provide better results in case of short length signal and undervalued lag order.

Klíčová slova

Autoregressive process, AIC, Burg method, Yule-Walker method, covariance method

Autoři

KLEJMOVÁ, E.

Vydáno

28. 4. 2016

Nakladatel

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

Místo

Brno

ISBN

978-80-214-5350-0

Kniha

Proceedings of the 22nd Conference STUDENT EEICT 2016

Číslo edice

1

Strany od

375

Strany do

379

Strany počet

5

BibTex

@inproceedings{BUT124486,
  author="Eva {Klejmová}",
  title="Evaluation of methods for AR coefficients estimation using monte carlo analysis",
  booktitle="Proceedings of the 22nd Conference STUDENT EEICT 2016",
  year="2016",
  number="1",
  pages="375--379",
  publisher="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  address="Brno",
  isbn="978-80-214-5350-0"
}