On identifiability of higher order block term tensor decompositions of rank Lr⊗ rank-1-Reference-Cited by-同舟云学术

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On identifiability of higher order block term tensor decompositions of rank Lr⊗ rank-1

Published:2018-07-31 Issue:2 Volume:68 Page:223-245
ISSN:0308-1087
Container-title:Linear and Multilinear Algebra
language:en
Short-container-title:Linear and Multilinear Algebra

Author:

Yang Ming¹,Li Wen²,Xiao Mingqing³

Affiliation:

1. Department of Computer Science, Southern Illinois University Carbondale, Carbondale, IL, USA

2. School of Mathematical Sciences, South China Normal University, Guangzhou, People's Republic of China

3. Department of Mathematics, Southern Illinois University Carbondale, Carbondale, IL, USA

Funder

NSF

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Algebra and Number Theory

Link

https://www.tandfonline.com/doi/pdf/10.1080/03081087.2018.1502251

Reference19 articles.

1. Tensor Decompositions for Signal Processing Applications: From two-way to multiway component analysis

2. Characterization of Extreme Points of Multi-Stochastic Tensors

3. Multiarray signal processing: Tensor decomposition meets compressed sensing

4. Blind Multilinear Identification

5. Decompositions of a Higher-Order Tensor in Block Terms—Part I: Lemmas for Partitioned Matrices

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1. Low-rank tensor recovery via non-convex regularization, structured factorization and spatio-temporal characteristics;Pattern Recognition;2023-05

2. $(L_r,L_r,1)$-Decompositions, Sparse Component Analysis, and the Blind Separation of Sums of Exponentials;SIAM Journal on Matrix Analysis and Applications;2022-06

3. 3-D Array Image Data Completion by Tensor Decomposition and Nonconvex Regularization Approach;IEEE Transactions on Signal Processing;2022

4. Nonlocal Low-Rank Tensor Completion for Visual Data;IEEE Transactions on Cybernetics;2021-02

5. Robust Graph Learning From Noisy Data;IEEE Transactions on Cybernetics;2020-05

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