Weighted Moore-Penrose inverses and fundamental theorem of even-order tensors with Einstein product

Jun JI , Yimin WEI

Front. Math. China ›› 2017, Vol. 12 ›› Issue (6) : 1319 -1337.

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Front. Math. China ›› 2017, Vol. 12 ›› Issue (6) : 1319 -1337. DOI: 10.1007/s11464-017-0628-1
RESEARCH ARTICLE
RESEARCH ARTICLE

Weighted Moore-Penrose inverses and fundamental theorem of even-order tensors with Einstein product

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Abstract

We treat even-order tensors with Einstein product as linear operators from tensor space to tensor space, define the null spaces and the ranges of tensors, and study their relationship. We extend the fundamental theorem of linear algebra for matrix spaces to tensor spaces. Using the new relationship, we characterize the least-squares (M) solutions to a multilinear system and establish the relationship between the minimum-norm (N) leastsquares (M) solution of a multilinear system and the weighted Moore-Penrose inverse of its coefficient tensor. We also investigate a class of even-order tensors induced by matrices and obtain some interesting properties.

Keywords

Fundamental theorem / weighted Moore-Penrose inverse / multilinear system / null space and range / tensor equation

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Jun JI, Yimin WEI. Weighted Moore-Penrose inverses and fundamental theorem of even-order tensors with Einstein product. Front. Math. China, 2017, 12(6): 1319-1337 DOI:10.1007/s11464-017-0628-1

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References

[1]

Ben-IsraelA, GrevilleT N E. Generalized Inverse: Theory and Applications.New York: John Wiley, 2003

[2]

BrazellM, LiN, NavascaC, TamonC. Solving multilinear systems via tensor inversion.SIAM J Matrix Anal Appl, 2013, 34: 542–570

[3]

BurdickD, McGownL, MillicanD, TuX. Resolution of multicomponent fluorescent mixtures by analysis of the excitation-emission-frequency array.J Chemometrics, 1990, 4: 15–28

[4]

ComonP. Tensor decompositions: State of the art and applications.In: McWhirter J G, Proudler I K, eds. Mathematics in Signal Processing, V. Oxford: Oxford Univ Press, 2001, 1–24

[5]

CooperJ, DutleA. Spectra of uniform hypergraphs.Linear Algebra Appl, 2012, 436: 3268–3292

[6]

EinsteinA. The foundation of the general theory of relativity.In: Kox A J, Klein M J, Schulmann R, eds. The Collected Papers of Albert Einstein. Princeton: Princeton Univ Press, 2007, 146–200

[7]

EldénL. Matrix Methods in Data Mining and Pattern Recognition.Philadelphia: SIAM, 2007

[8]

HuS, QiL. Algebraic connectivity of an even uniform hypergraph.J Comb Optim, 2012, 24: 564–579

[9]

KoldaT, BaderB. Tensor decompositions and applications.SIAM Review, 2009, 51: 455–500

[10]

LuoZ, QiL, YeY. Linear operators and positive semidefiniteness of symmetric tensors spaces.Sci China Math, 2015, 58: 197–212

[11]

SmildeA, BroR, GeladiP. Multi-Way Analysis: Applications in the Chemical Sciences.West Sussex: Wiley, 2004

[12]

SunL, ZhengB, BuC, WeiY. Moore-Penrose inverse of tensors via Einstein product.Linear Multilinear Algebra, 2016, 64: 686–698

[13]

VlasicD, BrandM, PfisterH, PopovicJ. Face transfer with multilinear models.ACM Trans Graphics, 2005, 24: 426–433

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