Recovering low‐rank tensor from limited coefficients in any ortho‐normal basis using tensor‐singular value decomposition

Recovering low‐rank tensor from limited coefficients in any ortho‐normal basis using tensor‐singular value decomposition

Abstract Tensor singular value decomposition (t‐SVD) provides a novel way to decompose a tensor. It has been employed mostly in recovering missing tensor entries from the observed tensor entries. The problem of applying t‐SVD to recover tensors from limited coefficients in any given ortho‐normal bas...

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Bibliographic Details
Main Authors: Shuli Ma, Jianhang Ai, Huiqian Du, Liping Fang, Wenbo Mei
Format: Article
Language:English
Published: Hindawi-IET 2021-05-01
Series:IET Signal Processing
Subjects:
biomedical MRI
image sampling
matrix algebra
medical image processing
singular value decomposition
tensors
Online Access:https://doi.org/10.1049/sil2.12017

Internet

https://doi.org/10.1049/sil2.12017

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