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Identification of switched linear regression models using sum-of-norms regularization

This paper proposes a general convex framework for the identification of switched linear systems. The proposed framework uses over-parameterization to avoid solving the otherwise combinatorially forbidding identification problem, and takes the form of a least-squares problem with a sum-of-norms regularization, a generalization of the ℓ1-regularization. The regularization constant regulates the complexity and is used to trade off the fit and the number of submodels. / <p>Funding Agencies|Swedish foundation for strategic research in the center MOVIII||Swedish Research Council in the Linnaeus center CADICS||European Research Council|267381|Sweden-America Foundation||Swedish Science Foundation||</p>

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-92612
Date January 2013
CreatorsOhlsson, Henrik, Ljung, Lennart
PublisherLinköpings universitet, Reglerteknik, Linköpings universitet, Tekniska högskolan, Linköpings universitet, Reglerteknik, Linköpings universitet, Tekniska högskolan, Elsevier
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeArticle in journal, info:eu-repo/semantics/article, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess
RelationAutomatica, 0005-1098, 2013, 49:4, s. 1045-1050

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