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A Multilinear Singular Value Decomposition
Open accessAbstract
We discuss a multilinear generalization of the singular value decomposition. There is a strong analogy between several properties of the matrix and the higher-order tensor decomposition; uniqueness, link with the matrix eigenvalue decomposition, first-order perturbation effects, etc., are analyzed. We investigate how tensor symmetries affect the decomposition and propose a multilinear generalization of the symmetric eigenvalue decomposition for pair-wise symmetric tensors.
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Metadata
- Authors
- De Lathauwer, L., De Moor, B., & Vandewalle, J.
- Venue
- SIAM Journal on Matrix Analysis and Applications
- Published
- 2000-01
- Volume
- 21
- Issue
- 4
- Pages
- 1253-1278
- ISSN
- 0895-4798 (ISSN-L)
- 1095-7162
- OpenAlex
- W2013912476
- Cited by
- 4,106
- References
- 0
- FWCI
- 5.16
- Type
- journal article
- Language
- en
- Open access
- green
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- De Lathauwer, L., De Moor, B., & Vandewalle, J. (2000). A Multilinear Singular Value Decomposition. SIAM Journal on Matrix Analysis and Applications. https://doi.org/10.1137/s0895479896305696
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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