Title :
Parameter estimation of continuous-time AR processes using integrated sampling
Author :
Fan, H. ; Soderstorm, T.
Author_Institution :
Dept. of Electr. & Comput. Eng., Cincinnati Univ., OH, USA
Abstract :
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
Keywords :
autoregressive processes; continuous time systems; least squares approximations; parameter estimation; consistent estimation; continuous-time AR processes; discrete-time data; integrated sampling; least squares method; parameter estimation; Additive noise; Computer simulation; Control systems; Instruments; Least squares approximation; Least squares methods; Noise robustness; Parameter estimation; Sampling methods; White noise;
Conference_Titel :
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4187-2
DOI :
10.1109/CDC.1997.652385
