Standard tensor and its applications in problem of singular values of tensors

Qingzhi YANG , Yiyong LI

Front. Math. China ›› 2019, Vol. 14 ›› Issue (5) : 967 -987.

PDF (334KB)
Front. Math. China ›› 2019, Vol. 14 ›› Issue (5) : 967 -987. DOI: 10.1007/s11464-019-0786-4
RESEARCH ARTICLE
RESEARCH ARTICLE

Standard tensor and its applications in problem of singular values of tensors

Author information +
History +
PDF (334KB)

Abstract

In this paper, first we give the definition of standard tensor. Then we clarify the relationship between weakly irreducible tensors and weakly irreducible polynomial maps by the definition of standard tensor. And we prove that the singular values of rectangular tensors are the special cases of the eigen-values of standard tensors related to rectangular tensors. Based on standard tensor, we present a generalized version of the weak Perron-Frobenius Theorem of nonnegative rectangular tensors under weaker conditions. Furthermore, by studying standard tensors, we get some new results of rectangular tensors. Besides, by using the special structure of standard tensors corresponding to nonnegative rectangular tensors, we show that the largest singular value is really geometrically simple under some weaker conditions.

Keywords

Standard tensor / nonnegative rectangular tensor / singular value / geometrically simple

Cite this article

Download citation ▾
Qingzhi YANG, Yiyong LI. Standard tensor and its applications in problem of singular values of tensors. Front. Math. China, 2019, 14(5): 967-987 DOI:10.1007/s11464-019-0786-4

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Bomze I M, Ling C, Qi L, Zhang X. Standard bi-quadratic optimization problems and unconstrained polynomial reformulations. J Global Optim, 2012, 52: 663–687

[2]

Chang K C, Pearson K, Zhang T. Perron Frobenius Theorem for nonnegative tensors. Commun Math Sci, 2008, 6(2): 507–520

[3]

Chang K C, Pearson K, Zhang T. Primitivity, the convergence of the NQZ method, and the largest eigenvalue for nonnegative tensors. SIAM J Matrix Anal Appl, 2011, 32(3): 806–819

[4]

Chang K C, Pearson K, Zhang T. Some variational principles for Z-eigenvalues of non- negative tensors. Linear Algebra Appl, 2013, 438(11): 4166–4182

[5]

Chang K C, Qi L, Zhang T. A survey on the spectral theory of nonnegative tensors. Numer Linear Algebra Appl, 2013, 20(6): 891–912

[6]

Chang K C, Qi L, Zhou G. Singular values of a real rectangular tensor. J Math Anal Appl, 2010, 370: 284–294

[7]

Chang K C, Zhang T. Multiplicity of singular values for tensors. Commun Math Sci, 2009, 7(3): 611–625

[8]

Dahl G, Leinaas J M, Myrheim J, Ovrum E. A tensor product matrix approximation problem in quantum physics. Linear Algebra Appl, 2007, 420: 711–725

[9]

De Lathauwer L, De Moor B, Vandewalle J. On the best rank-1 and rank-(R1, R2, . . . , RN) approximation of higher-order tensors. SIAM J Matrix Anal Appl, 2000, 21(4): 1324–1342

[10]

Friedland S, Gaubert S, Han L. Perron-Frobenius theorem for nonnegative multilinear forms and extensions. Linear Algebra Appl, 2013, 438(2): 738–749

[11]

Hu S, Huang Z, Qi L. Strictly nonnegative tensors and nonnegative tensor partition. Sci China Math, 2014, 57(1): 181–195

[12]

Hu S, Qi L. Algebraic connectivity of an even uniform hypergraph. J Comb Optim, 2012, 24: 564–579

[13]

Lim L H. Singular values and eigenvalues of tensors: a variational approach. In: Proc of the IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing. 2005, 129–132

[14]

Lim L H. Multilinear pagerank: measuring higher order connectivity in linked objects. The Internet: Today and Tomorrow, 2005

[15]

Ling C, Zhang X, Qi L. Semidefinite relaxation approximation for multivariate bi- quadratic optimization with quadratic constraints. Numer Linear Algebra Appl, 2011, 19: 113–131

[16]

Ng M, Qi L, Zhou G. Finding the largest eigenvalue of a non-negative tensor. SIAM J Matrix Anal Appl, 2009, 31(3): 1090–1099

[17]

Ni Q, Qi L, Wang F. An eigenvalue method for the positive definiteness identification problem. IEEE Trans Automat Control, 2008, 53(5): 1096–1107

[18]

Pearson K. Essentially positive tensors. Int J Algebra, 2010, 4: 421–427

[19]

Qi L. Eigenvalues of a real supersymmetric tensor. J Symbolic Comput, 2005, 40(6): 1302–1324

[20]

Qi L, Dai H-H, Han D. Conditions for strong ellipticity and M-eigenvalues. Front Math China, 2009, 4(2): 349–364

[21]

Qi L, Sun W, Wang Y. Numerical multilinear algebra and its applications. Front Math China, 2007, 2(4): 501–526

[22]

Qi Y, Comon P, Lim L H. Uniqueness of nonnegative tensor approximations. IEEE Trans Inform Theory, 2016, 62(4): 2170–2183

[23]

Ragnarsson S, Van Loan C F. Block tensors and symmetric embeddings. Linear Algebra Appl, 2013, 438(2): 853–874

[24]

Yang Q, Yang Y. Further results for Perron-Frobenius Theorem for nonnegative tensors II. SIAM J Matrix Anal Appl, 2011, 32(4): 1236–1250

[25]

Yang Y, Yang Q. Further results for PerronCFrobenius theorem for nonnegative tensors. SIAM J Matrix Anal Appl, 2010, 31(5): 2517–2530

[26]

Yang Y, Yang Q. Singular values of nonnegative rectangular tensors. Front Math China, 2011, 6(2): 363–378

[27]

Yang Y, Yang Q. A note on the geometric simplicity of the spectral radius of non- negative irreducible tensor. arXiv: 1101.2479

[28]

Zhang X, Ling C, Qi L. Semidefinite relaxation bounds for bi-quadratic optimization problems with quadratic constraints. J Global Optim, 2010, 49: 293–311

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature

AI Summary AI Mindmap
PDF (334KB)

573

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/