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Identification of sparse linear regression
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
1995 (English)Report (Other academic)
Abstract [en]

Some important practical signals and systems can be modeled by very large linear regression models where it is reasonable that most of the parameters are zero We give an ecient method to solve this combined estimation and struc ture determination problem and relate the result to Akaikes information criteria for structure selection and criteria based on hypothesis testing A recursive algorithm is derived which can be applied to timevarying systems as well Two practical examples show the eciency of the approach

Place, publisher, year, edition, pages
Linköping: Linköping University , 1995. , 6 p.
LiTH-ISY-R, ISSN 1400-3902 ; 1788
Keyword [en]
Linear regression, Structure selection, Maximum likelihood, Spase models, Echoes, Orthonormal bases
Keyword [sv]
Deskriptiv Statistik Multivariat Analys-, Cybernetik Informationsteori
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-55279ISRN: LiTH-ISY-R-1788OAI: diva2:315846
Available from: 2010-04-29 Created: 2010-04-29 Last updated: 2014-10-06Bibliographically approved

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Gustafsson, Fredrik
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Automatic ControlThe Institute of Technology
Control Engineering

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