Singular values of nonnegative rectangular tensors

Yuning YANG, Qingzhi YANG

Front. Math. China ›› 2011, Vol. 6 ›› Issue (2) : 363-378.

PDF(209 KB)
PDF(209 KB)
Front. Math. China ›› 2011, Vol. 6 ›› Issue (2) : 363-378. DOI: 10.1007/s11464-011-0108-y
RESEARCH ARTICLE
RESEARCH ARTICLE

Singular values of nonnegative rectangular tensors

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Abstract

The real rectangular tensors arise from the strong ellipticity condition problem in solid mechanics and the entanglement problem in quantum physics. Some properties concerning the singular values of a real rectangular tensor were discussed by K. C. Chang et al. [J. Math. Anal. Appl., 2010, 370: 284-294]. In this paper, we give some new results on the Perron-Frobenius Theorem for nonnegative rectangular tensors. We show that the weak Perron-Frobenius keeps valid and the largest singular value is really geometrically simple under some conditions. In addition, we establish the convergence of an algorithm proposed by K. C. Chang et al. for finding the largest singular value of nonnegative primitive rectangular tensors.

Keywords

Nonnegative rectangular tensor / Perron-Frobenius Theorem / singular value / algorithm

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Yuning YANG, Qingzhi YANG. Singular values of nonnegative rectangular tensors. Front Math Chin, 2011, 6(2): 363‒378 https://doi.org/10.1007/s11464-011-0108-y

References

[1]
Bloy L, Verma R. On computing the underlying fiber directions from the diffusion orientation distribution function. In: Metaxas D, Axel L, Fichtinger G, Székely G, eds. Medical Image Computing and Computer-Assisted Intervention-MICCAI 2008. Lecture Notes in Computer Science, No 5241. Berlin/Heidelberg: Springer, 2008, 1-8
CrossRef Google scholar
[2]
Chang K C, Pearson K, T. Zhang T. Perron Frobenius Theorem for nonnegative tensors. Comm Math Sci, 2008, 6: 507-520
[3]
Chang K C, Qi L, Zhou G. Singular values of a real rectangular tensor. J Math Anal Appl, 2010, 370: 284-294
CrossRef Google scholar
[4]
Drineas P, Lim L H. A multilinear spectral theory of hypergraphs and expander hypergraphs. 2005
[5]
Lathauwer L D, Moor B D, Vandewalle J. On the best rank-1 and rank-(R1, R2, . . . , RN) approximation of higher-order tensors. SIAM J Matrix Anal Appl, 2000, 21: 1324-1342
CrossRef Google scholar
[6]
Lim L H. Singular values and eigenvalues of tensors: a variational approach. Proceedings of the IEEE InternationalWorkshop on Computational Advances in Multi-Sensor Adaptive Processing, 2005, 1: 129-132
[7]
Lim L H. Multilinear pagerank: measuring higher order connectivity in linked objects. The Internet: Today and Tomorrow, <month>July</month>, 2005
[8]
Ng M, Qi L, Zhou G. Finding the largest eigenvalue of a non-negative tensor. SIAM J Matrix Anal Appl, 2009, 31: 1090-1099
CrossRef Google scholar
[9]
Ni Q, Qi L, Wang F. An eigenvalue method for the positive definiteness identification problem. IEEE Transactions on Automatic Control, 2008, 53: 1096-1107
CrossRef Google scholar
[10]
Pearson K. Essentially positive tensors. Int J Algebra, 2010, 4: 421-427
[11]
Pearson K. Primitive tensors and convergence of an iterative process for the eigenvalues of a primitive tensor. arXiv: 1004.2423v1, 2010
[12]
Qi L. Eigenvalues of a real supersymmetric tensor. J Symb Comput, 2005, 40: 1302-1324
CrossRef Google scholar
[13]
Qi L, Sun W, Wang Y. Numerical multilinear algebra and its applications. Front Math China, 2007, 2(4): 501-526
CrossRef Google scholar
[14]
Qi L, Wang Y, Wu E. D-eigenvalues of diffusion kurtosis tensor. J Comput Appl Math, 2008, 221: 150-157
CrossRef Google scholar
[15]
Yang Y, Yang Q. Further results for Perron-Frobenius Theorem for nonnegative tensors. SIAM J Matrix Anal Appl, 2010, 31: 2517-2530
CrossRef Google scholar
[16]
Yang Y, Yang Q. A note on the geometric simplicity of the spectral radius of nonnegative irreducible tensor. http://arxiv.org/abs/1101.2479v1, 2010

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