File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Symmetric Tensor Decomposition by an Iterative Eigendecomposition Algorithm

TitleSymmetric Tensor Decomposition by an Iterative Eigendecomposition Algorithm
Authors
Issue Date2016
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/cam
Citation
Journal of Computational and Applied Mathematics, 2016, v. 308, p. 69-82 How to Cite?
AbstractWe present an iterative algorithm, called the symmetric tensor eigen-rank-one iterative decomposition (STEROID), for decomposing a symmetric tensor into a real linear combination of symmetric rank-1 unit-norm outer factors using only eigendecompositions and least-squares fitting. Originally designed for a symmetric tensor with an order being a power of two, STEROID is shown to be applicable to any order through an innovative tensor embedding technique. Numerical examples demonstrate the high efficiency and accuracy of the proposed scheme even for large scale problems. Furthermore, we show how STEROID readily solves a problem in nonlinear block-structured system identification and nonlinear state-space identification.
Persistent Identifierhttp://hdl.handle.net/10722/229180
ISSN
2015 Impact Factor: 1.328
2015 SCImago Journal Rankings: 1.089

 

DC FieldValueLanguage
dc.contributor.authorBatselier, K-
dc.contributor.authorWong, N-
dc.date.accessioned2016-08-23T14:09:30Z-
dc.date.available2016-08-23T14:09:30Z-
dc.date.issued2016-
dc.identifier.citationJournal of Computational and Applied Mathematics, 2016, v. 308, p. 69-82-
dc.identifier.issn0377-0427-
dc.identifier.urihttp://hdl.handle.net/10722/229180-
dc.description.abstractWe present an iterative algorithm, called the symmetric tensor eigen-rank-one iterative decomposition (STEROID), for decomposing a symmetric tensor into a real linear combination of symmetric rank-1 unit-norm outer factors using only eigendecompositions and least-squares fitting. Originally designed for a symmetric tensor with an order being a power of two, STEROID is shown to be applicable to any order through an innovative tensor embedding technique. Numerical examples demonstrate the high efficiency and accuracy of the proposed scheme even for large scale problems. Furthermore, we show how STEROID readily solves a problem in nonlinear block-structured system identification and nonlinear state-space identification.-
dc.languageeng-
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/cam-
dc.relation.ispartofJournal of Computational and Applied Mathematics-
dc.rightsPosting accepted manuscript (postprint): © <2016>. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleSymmetric Tensor Decomposition by an Iterative Eigendecomposition Algorithm-
dc.typeArticle-
dc.identifier.emailBatselier, K: kbatseli@hku.hk-
dc.identifier.emailWong, N: nwong@eee.hku.hk-
dc.identifier.authorityWong, N=rp00190-
dc.description.naturepostprint-
dc.identifier.doi10.1016/j.cam.2016.05.024-
dc.identifier.hkuros260149-
dc.identifier.volume308-
dc.identifier.spage69-
dc.identifier.epage82-
dc.publisher.placeNetherlands-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats