DocumentCode
176981
Title
Asymptotical behavior of parameter estimation in prediction error framework
Author
Caiyun Chen ; Zhibin Yan
Author_Institution
Natural Sci. Res. Center, Harbin Inst. of Technol., Harbin, China
fYear
2014
fDate
May 31 2014-June 2 2014
Firstpage
4496
Lastpage
4500
Abstract
In prediction error method, it is known that the sequence of the criterion function converges uniformly in the parameter with probability one as the length of the input-output data tends to infinity. When the minimizing points of the limiting function criterion are not unique, the convergence of parameter estimation is not guaranteed in general. Two cases are distinguished. The case one is that the set of the minimizing points of the limiting function criterion is a continuum, and the case two is that the points of that set are isolated. Some interesting phenomena relating to the different cases are shown about the asymptotical behavior of parameter estimation through examples and theoretical analysis.
Keywords
convergence; parameter estimation; probability; asymptotical behavior; convergence; criterion function; input-output data; limiting function criterion; parameter estimation; prediction error framework; prediction error method; probability; Convergence; Estimation; Limiting; Measurement; Parameter estimation; Vectors; White noise; Hausdorff metric; parameter estimation; prediction error method; system identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location
Changsha
Print_ISBN
978-1-4799-3707-3
Type
conf
DOI
10.1109/CCDC.2014.6852974
Filename
6852974
Link To Document