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Solving bilinear tensor least squares problems and application to Hammerstein identification
Linköping University, Department of Mathematics, Computational Mathematics. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-2281-856X
Skolkovo Inst Sci and Technol Skoltech, Russia.
2019 (English)In: Numerical Linear Algebra with Applications, ISSN 1070-5325, E-ISSN 1099-1506, Vol. 26, no 2, article id e2226Article in journal (Refereed) Published
Abstract [en]

Bilinear tensor least squares problems occur in applications such as Hammerstein system identification and social network analysis. A linearly constrained problem of medium size is considered, and nonlinear least squares solvers of Gauss-Newton-type are applied to numerically solve it. The problem is separable, and the variable projection method can be used. Perturbation theory is presented and used to motivate the choice of constraint. Numerical experiments with Hammerstein models and random tensors are performed, comparing the different methods and showing that a variable projection method performs best.

Place, publisher, year, edition, pages
WILEY , 2019. Vol. 26, no 2, article id e2226
Keywords [en]
bilinear regression; bilinear tensor least squares problem; Hammerstein identification; Gauss-Newton-type method; separable; variable projection
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-154538DOI: 10.1002/nla.2226ISI: 000457614700006OAI: oai:DiVA.org:liu-154538DiVA, id: diva2:1290534
Note

Funding Agencies: Mega Grant, Grant/Award Number:14.756.31.0001

Available from: 2019-02-20 Created: 2019-02-20 Last updated: 2019-03-26

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The full text will be freely available from 2019-12-10 11:40
Available from 2019-12-10 11:40

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