Criteria for strong H-tensors

Yiju WANG , Kaili ZHANG , Hongchun SUN

Front. Math. China ›› 2016, Vol. 11 ›› Issue (3) : 577 -592.

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Front. Math. China ›› 2016, Vol. 11 ›› Issue (3) : 577 -592. DOI: 10.1007/s11464-016-0525-z
RESEARCH ARTICLE
RESEARCH ARTICLE

Criteria for strong H-tensors

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Abstract

H-tensor is a new developed concept which plays an important role in tensor analysis and computing. In this paper, we explore the properties of H-tensors and establish some new criteria for strong H-tensors. In particular, based on the principal subtensor, we provide a new necessary and sufficient condition of strong H-tensors, and based on a type of generalized diagonal product dominance, we establish some new criteria for identifying strong H-tensors. The results obtained in this paper extend the corresponding conclusions for strong H-matrices and improve the existing results for strong H-tensors.

Keywords

Strong H-tensor / generalized diagonal dominance / multilinear algebra / weak irreducibility

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Yiju WANG, Kaili ZHANG, Hongchun SUN. Criteria for strong H-tensors. Front. Math. China, 2016, 11(3): 577-592 DOI:10.1007/s11464-016-0525-z

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References

[1]

Barmpoutis A, Vemuri B C, Howland D, Forder J R. Regularized positive-definite fourth order tensor field estimation from DW-MRI. Neuroimage, 2009, 45: 153–162

[2]

Barmpoutis A, Vemuri B C, Shepherd T M, Forder J R. Tensor splines for interpolation and approximation of DT-MRI with applications to segmentation of isolated rat hippocampi. Transactions on Medical Imaging, 2007, 26: 1537–1546

[3]

Basser P J, Jones D K. Diffusion-tensor MRI: theory, experimental design and data analysis—a technical review. NMR Biomed, 2002, 15: 456–467

[4]

Basser P J, Mattiello J, LeBihan D. Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson B, 1994, 103: 247–254

[5]

Brachat J, Comon P, Mourrain B, Tsigaridas E. Symmetric tensor decomposition. Linear Algebra Appl, 2010, 433: 1851–1872

[6]

Chang K, Pearson K, Zhang T. Perron-Frobenius theorem for nonnegative tensors. Commun Math Sci, 2008, 6: 507–520

[7]

Chen H, Qi L. Positive definiteness and semi-definiteness of even order symmetric Cauchy tensors. J Ind Manag Optim, 2015, 11: 1263–1274

[8]

Cichocki A, Zdunek R, Huy P, Amari S. Nonnegative Matrix and Tensor Factorizations. New York: John Wiley & Sons, Ltd, 2009

[9]

De Lathauwer L, De Moor B, Vandewalle J. A multilinear singular value decomposition. SIAM J Matrix Anal Appl, 2010, 21: 1253–1278

[10]

Ding W, Qi L, Wei Y. M-tensors and nonsingular M-tensors. Linear Algebra Appl, 2013, 439: 3264–3278

[11]

Gandy S, Recht B, Yamada I. Tensor completion and low-n-rank tensor recovery via convex optimization. Inverse Problems, 2011, 27: 025010

[12]

Horn R A, Johnson C R. Matrix Analysis. Cambridge: Cambridge University Press, 1985

[13]

Hu S, Huang Z, Qi L. Strictly nonnegative tensors and nonnegative tensor partition. Sci China Math, 2014, 57: 181–195

[14]

Kannan M R, Shaked-Monderer N, Berman A. Some properties of strong H-tensors and general H-tensors, Linear Algebra Appl, 2015, 476: 42–55

[15]

Kofidis E, Regalia P A. On the best rank-1 approximation of higher-order supersymmetric tensors, SIAM J Matrix Anal Appl, 2002, 23: 863–884

[16]

Kolda T G, Bader B W. Tensor decompositions and applications. SIAM Review, 2009, 51: 455–500

[17]

Li C, Wang F, Zhao J, Zhu Y, Li Y. Criterions for the positive definiteness of real supersymmetric tensors. J Comput Appl Math, 2014, 255: 1–14

[18]

Li Y, Liu Q, Qi L. Criteria for strong H-tensor. 2015, preprint

[19]

Nikias C L, Mendel J M. Signal processing with higher-order spectra. IEEE Signal Processing Magazine, 1993, 10: 10–37

[20]

Qi L. Eigenvalues of a real supersymmetric tensor. J Symbolic Comput, 2005, 40: 1302–1324

[21]

Qi L, Yu G, Wu E X. Higher order positive semidefinite diffusion tensor imaging. SIAM J Imaging Sci, 2010, 3: 416–433

[22]

Qi L, Xu C, Xu Y. Nonnegative tensor factorization, completely positive tensors and a Hierarchically elimination algorithm. SIAM J Matrix Anal Appl, 2014, 35: 1227–1241

[23]

Song Y, Qi L. Infinite and finite dimensional Hilbert tensors. Linear Algebra Appl, 2014, 451: 1–14

[24]

Song Y, Qi L. Necessary and sufficient conditions for copositive tensors. Linear Multilinear Algebra, 2015, 63: 120–131

[25]

Wang Y, Zhou G, Caccetta L. Nonsingular H-tensor and its criteria. J Ind Manag Optim, 2016, 12(4): 1173–1186

[26]

Yang Y, Yang Q. Further results for Perron-Frobenius theorem for nonnegative tensors. SIAM J Matrix Anal Appl, 2010, 31: 2517–2530

[27]

Zhang L, Qi L, Zhou G. M-tensors and some applications. SIAM J Matrix Anal Appl, 2014, 35: 437–452

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