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Structure-preserving low multilinear rank approximation of antisymmetric tensors (CROSBI ID 240215)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Begović Kovač, Erna ; Kressner, Daniel Structure-preserving low multilinear rank approximation of antisymmetric tensors // SIAM journal on matrix analysis and applications, 38 (2017), 3; 967-983. doi: 10.1137/16M106618X

Podaci o odgovornosti

Begović Kovač, Erna ; Kressner, Daniel

engleski

Structure-preserving low multilinear rank approximation of antisymmetric tensors

This paper is concerned with low multilinear rank approximations to antisymmetric tensors, that is, multivariate arrays for which the entries change sign when permuting pairs of indices. We show which ranks can be attained by an antisymmetric tensor and discuss the adaption of existing approximation algorithms to preserve antisymmetry, most notably a Jacobi algorithm. Particular attention is paid to the important special case when choosing the rank equal to the order of the tensor. It is shown that this case can be addressed with an unstructured rank-$1$ approximation. This allows for the straightforward application of the higher-order power method, for which we discuss effective initialization strategies.

Tensor ; antisymmetric ; low rank ; singular value decomposition ; Jacobi rotation

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Podaci o izdanju

38 (3)

2017.

967-983

objavljeno

0895-4798

10.1137/16M106618X

Povezanost rada

Matematika

Poveznice
Indeksiranost