Title :
Model validation methods for errors-in-variables estimation
Author :
Soderstrom, Torsten ; Yuz, Juan
Author_Institution :
Dept. of Inf. Technol., Uppsala Univ., Uppsala, Sweden
Abstract :
When identifying a dynamic system the model has to be validated as well. For an errors-in-variables situation where both input and output measurements are noise corrupted, this is a nontrivial task, seldom treated in the literature. Some different approaches for model validation are introduced and evaluated by theoretical analysis as well as application to simulated data.
Keywords :
estimation theory; identification; measurement errors; dynamic system identification; errors-in-variables estimation; input measurements; model validation methods; noise corruption; output measurements; Analytical models; Computational modeling; Data models; Numerical models; Vectors; White noise;
Conference_Titel :
Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
Conference_Location :
Firenze
Print_ISBN :
978-1-4673-5714-2
DOI :
10.1109/CDC.2013.6760482
