Sökning: onr:"swepub:oai:DiVA.org:liu-152415" >
Input selection in ...
Input selection in ARX model estimation using group lasso regularization
-
- Klingspor, Måns (författare)
- Linköpings universitet,Reglerteknik,Tekniska fakulteten
-
- Hansson, Anders (författare)
- Linköpings universitet,Reglerteknik,Tekniska fakulteten
-
- Löfberg, Johan (författare)
- Linköpings universitet,Reglerteknik,Tekniska fakulteten
-
(creator_code:org_t)
- ELSEVIER SCIENCE BV, 2018
- 2018
- Engelska.
-
Ingår i: 18th IFAC Symposium on System Identification (SYSID), Proceedings. - : ELSEVIER SCIENCE BV. ; , s. 897-902
- Relaterad länk:
-
https://doi.org/10.1...
-
visa fler...
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
visa färre...
Abstract
Ämnesord
Stäng
- In system identification, input selection is a challenging problem. Since less complex models are desireable, non-relevant inputs should be methodically and correctly discarded before or under the estimation process. In this paper we investigate an input selection extension in least-squares ARX estimation and show that better model estimates are achieved compared to the least-square ssolution, in particular, for short batches of estimation data. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
Nyckelord
- Input selection; System identification; ARX-models; ARMAX-models; Signal-to-noise ratio
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)