Generalized tensor function via the tensor singular value decomposition based on the T-product

In this paper, we present the definition of generalized tensor function according to the tensor singular value decomposition (T-SVD) based on the tensor T-product. Also, we introduce the compact singular value decomposition (T-CSVD) of tensors, from which the projection operators and Moore-Penrose i...

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Published inLinear algebra and its applications Vol. 590; pp. 258 - 303
Main Authors Miao, Yun, Qi, Liqun, Wei, Yimin
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier Inc 01.04.2020
American Elsevier Company, Inc
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Abstract In this paper, we present the definition of generalized tensor function according to the tensor singular value decomposition (T-SVD) based on the tensor T-product. Also, we introduce the compact singular value decomposition (T-CSVD) of tensors, from which the projection operators and Moore-Penrose inverse of tensors are obtained. We establish the Cauchy integral formula for tensors by using the partial isometry tensors and apply it into the solution of tensor equations. Then we establish the generalized tensor power and the Taylor expansion of tensors. Explicit generalized tensor functions are listed. We define the tensor bilinear and sesquilinear forms and propose theorems on structures preserved by generalized tensor functions. For complex tensors, we established an isomorphism between complex tensors and real tensors. In the last part of our paper, we find that the block circulant operator establishes an isomorphism between tensors and matrices. This isomorphism is used to prove the F-stochastic structure is invariant under generalized tensor functions. The concept of invariant tensor cones is raised.
AbstractList In this paper, we present the definition of generalized tensor function according to the tensor singular value decomposition (T-SVD) based on the tensor T-product. Also, we introduce the compact singular value decomposition (T-CSVD) of tensors, from which the projection operators and Moore-Penrose inverse of tensors are obtained. We establish the Cauchy integral formula for tensors by using the partial isometry tensors and apply it into the solution of tensor equations. Then we establish the generalized tensor power and the Taylor expansion of tensors. Explicit generalized tensor functions are listed. We define the tensor bilinear and sesquilinear forms and propose theorems on structures preserved by generalized tensor functions. For complex tensors, we established an isomorphism between complex tensors and real tensors. In the last part of our paper, we find that the block circulant operator establishes an isomorphism between tensors and matrices. This isomorphism is used to prove the F-stochastic structure is invariant under generalized tensor functions. The concept of invariant tensor cones is raised.
Author Qi, Liqun
Wei, Yimin
Miao, Yun
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Keywords T-product
Complex-to-real isomorphism
Tensor bilinear form
T-CSVD
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Generalized tensor function
Moore-Penrose inverse
Jordan algebra
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Cauchy integral formula
Tensor-to-matrix isomorphism
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Lie algebra
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T-SVD
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Snippet In this paper, we present the definition of generalized tensor function according to the tensor singular value decomposition (T-SVD) based on the tensor...
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SubjectTerms Block tensor multiplication
Cauchy integral formula
Complex-to-real isomorphism
Cones
Decomposition
Generalized tensor function
Invariants
Isomorphism
Jordan algebra
Lie algebra
Linear algebra
Mathematical analysis
Moore-Penrose inverse
Operators (mathematics)
Singular value decomposition
T-CSVD
T-product
T-SVD
Taylor series
Tensor bilinear form
Tensor-to-matrix isomorphism
Tensors
Title Generalized tensor function via the tensor singular value decomposition based on the T-product
URI https://dx.doi.org/10.1016/j.laa.2019.12.035
https://www.proquest.com/docview/2376728830
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