Regressor and Structure Selection in NARX Models Using a Structured ANOVA Approach
2007 (English)Report (Other academic)
Regressor selection can be viewed as the first step in the system identification process. The benefits of finding good regressors before estimating complex models are especially clear for nonlinear systems, where the class of possible models is huge. In this article, a structured way of using the tool analysis of variance (ANOVA) is presented and used for NARX model (nonlinear autoregressive model with exogenous input) identification with many candidate regressors.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2007. , 16 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2799
Analysis of variance, Nonlinear system identification, Structure identification
IdentifiersURN: urn:nbn:se:liu:diva-55832ISRN: LiTH-ISY-R-2799OAI: oai:DiVA.org:liu-55832DiVA: diva2:316706