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Article: Symmetric Tensor Decomposition by an Iterative Eigendecomposition Algorithm
Title | Symmetric Tensor Decomposition by an Iterative Eigendecomposition Algorithm |
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Authors | |
Keywords | Decomposition Eigendecomposition Least-squares Rank-1 Symmetric tensor |
Issue Date | 2016 |
Publisher | Elsevier 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? |
Abstract | We 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 Identifier | http://hdl.handle.net/10722/229180 |
ISSN | 2023 Impact Factor: 2.1 2023 SCImago Journal Rankings: 0.858 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Batselier, K | - |
dc.contributor.author | Wong, N | - |
dc.date.accessioned | 2016-08-23T14:09:30Z | - |
dc.date.available | 2016-08-23T14:09:30Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Journal of Computational and Applied Mathematics, 2016, v. 308, p. 69-82 | - |
dc.identifier.issn | 0377-0427 | - |
dc.identifier.uri | http://hdl.handle.net/10722/229180 | - |
dc.description.abstract | We 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.language | eng | - |
dc.publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/cam | - |
dc.relation.ispartof | Journal of Computational and Applied Mathematics | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Decomposition | - |
dc.subject | Eigendecomposition | - |
dc.subject | Least-squares | - |
dc.subject | Rank-1 | - |
dc.subject | Symmetric tensor | - |
dc.title | Symmetric Tensor Decomposition by an Iterative Eigendecomposition Algorithm | - |
dc.type | Article | - |
dc.identifier.email | Batselier, K: kbatseli@hku.hk | - |
dc.identifier.email | Wong, N: nwong@eee.hku.hk | - |
dc.identifier.authority | Wong, N=rp00190 | - |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1016/j.cam.2016.05.024 | - |
dc.identifier.scopus | eid_2-s2.0-84975141180 | - |
dc.identifier.hkuros | 260149 | - |
dc.identifier.volume | 308 | - |
dc.identifier.spage | 69 | - |
dc.identifier.epage | 82 | - |
dc.identifier.isi | WOS:000381546600006 | - |
dc.publisher.place | Netherlands | - |
dc.identifier.issnl | 0377-0427 | - |