Original title: Evaluation of Methods for AR Coefficients Estimation Using Monte Carlo Analysis
Authors: Klejmova, Eva
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: 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 performance 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.
Keywords: AIC; Autoregressive process; Burg method; covariance method; Yule-Walker method
Host item entry: Proceedings of the 22nd Conference STUDENT EEICT 2016, ISBN 978-80-214-5350-0

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/83959

Permalink: http://www.nusl.cz/ntk/nusl-613828


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