Parameter estimation of continuous-time AR processes using integrated sampling

In this short paper we study estimation of continuous-time AR process parameters from discrete-time data obtained by integrated sampling. The method used is the least squares. Conditions are derived for consistent estimation. Computer simulation shows that the LS method gives comparable performance...

Full description

Saved in:
Bibliographic Details
Published inProceedings of the 36th IEEE Conference on Decision and Control Vol. 4; pp. 3474 - 3475 vol.4
Main Authors Fan, H., Soderstorm, T.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1997
Subjects
Additive noise
Computer simulation
Control systems
Instruments
Least squares approximation
Least squares methods
Noise robustness
Parameter estimation
Sampling methods
White noise
Online AccessGet full text
ISBN0780341872
9780780341876
ISSN0191-2216
DOI10.1109/CDC.1997.652385

Cover

More Information
Summary:In this short paper we study estimation of continuous-time AR process parameters from discrete-time data obtained by integrated sampling. The method used is the least squares. Conditions are derived for consistent estimation. Computer simulation shows that the LS method gives comparable performance with previous LS results which use instantaneous sampling.
ISBN:0780341872
9780780341876
ISSN:0191-2216
DOI:10.1109/CDC.1997.652385