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T-Jordan Canonical Form and T-Drazin Inverse Based on the T-Product

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TLDR
In this article, the T-Jordan canonical form and its properties are investigated for tensor similarity and the concepts of Tminimal polynomial and T-characteristic polynomials are proposed.
Abstract
In this paper, we investigate the tensor similarity and propose the T-Jordan canonical form and its properties. The concepts of the T-minimal polynomial and the T-characteristic polynomial are proposed. As a special case, we present properties when two tensors commute based on the tensor T-product. We prove that the Cayley–Hamilton theorem also holds for tensor cases. Then, we focus on the tensor decompositions: T-polar, T-LU, T-QR and T-Schur decompositions of tensors are obtained. When an F-square tensor is not invertible with the T-product, we study the T-group inverse and the T-Drazin inverse which can be viewed as the extension of matrix cases. The expressions of the T-group and T-Drazin inverses are given by the T-Jordan canonical form. The polynomial form of the T-Drazin inverse is also proposed. In the last part, we give the T-core-nilpotent decomposition and show that the T-index and T-Drazin inverses can be given by a limit process.

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Journal ArticleDOI

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

TL;DR: In this paper, a generalized tensor function according to the tensor singular value decomposition (T-SVD) is defined, from which the projection operators and Moore-Penrose inverse of tensors are obtained.
Posted Content

Generalized Tensor Function via the Tensor Singular Value Decomposition based on the T-Product

TL;DR: It is found that the block circulant operator established an isomorphism between tensors and matrices that is used to prove the F-stochastic structure is invariant under generalized tensor functions.
Journal ArticleDOI

T-positive semidefiniteness of third-order symmetric tensors and T-semidefinite programming

TL;DR: In this paper, the T-positive semidefinite programming over the space of third-order symmetric tensors (TSDP) was introduced, which is an analogue to the widely used SDP relaxation.
Journal ArticleDOI

Perturbation bounds for DMP and CMP inverses of tensors via Einstein product

TL;DR: In this paper, the DMP and CMP inverses of tensors via Einstein product are defined and some characterizations, representations, and properties for these generalized inverse are investigated.
Journal ArticleDOI

A study on T-eigenvalues of third-order tensors

TL;DR: In this article, the T-eigenvalues of third-order tensors are studied and a commutative tensor family is proposed, including Hermitian tensors.
References
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Book

Matrix computations

Gene H. Golub
Book

Generalized inverses: theory and applications

TL;DR: In this paper, the Moore of the Moore-Penrose Inverse is described as a generalized inverse of a linear operator between Hilbert spaces, and a spectral theory for rectangular matrices is proposed.
MonographDOI

Functions of Matrices: Theory and Computation

TL;DR: A thorough and elegant treatment of the theory of matrix functions and numerical methods for computing them, including an overview of applications, new and unpublished research results, and improved algorithms.
Book

Generalized inverses of linear transformations

TL;DR: In this article, the Moore-Penrose or generalized inverse has been applied to the theory of finite Markov chains, and applications of the Drazin inverse have been discussed.
Journal ArticleDOI

Third-Order Tensors as Operators on Matrices: A Theoretical and Computational Framework with Applications in Imaging

TL;DR: This paper investigates further implications including a bilinear operator on the matrices which is nearly an inner product and which leads to definitions for length ofMatrices, angle between two matrices, and orthogonality of matrices and the use of t-linear combinations to characterize the range and kernel of a mapping defined by a third-order tensor and the t-product and the quantification of the dimensions of those sets.
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