Triangular Decomposition of CP Factors of a Third-Order Tensor with Application to Solving Nonlinear Systems of Equations

Bozorgmanesh, Hassan; Hajarian, Masoud

doi:10.1007/s10915-021-01758-8

Cited by 5 publications

(1 citation statement)

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“…Here, our focus is on CP decomposition and higher-order INDSCAL. Since their introduction, tensor decompositions have been used in psychometrics, chemometrics, signal processing, image processing and solving nonlinear systems of equations [21,16,22,4].…”

Section: Introductionmentioning

confidence: 99%

On rank decomposition and semi-symmetric rank decomposition of semi-symmetric tensors

Bozorgmanesh

Chronopoulos

2022

CMCMA

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A tensor is called semi-symmetric if all modes but one, are symmetric. In this paper, we study the CP decomposition of semi-symmetric tensors or higher-order individual difference scaling (INDSCAL). Comon's conjecture states that for any symmetric tensor, the CP rank and symmetric CP rank are equal, while it is known that Comon's conjecture is not true in the general case but it is proved under several assumptions in the literature. In the paper, Comon's conjecture is extended for semi-symmetric CP decomposition and CP decomposition of semi-symmetric tensors under suitable assumptions. Specially, we show that if a semi-symmetric tensor has a CP rank smaller or equal to its order, or when the semi-symmetric CP rank is less than/or equal to the dimension, then the semi-symmetric CP rank is equal to the CP rank.

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Section: Introductionmentioning

confidence: 99%