THE RATE OF CONVERGENCE AND WEAKER CONVERGENT CONDITION FOR THE METHOD FOR FINDING THE LARGEST SINGULAR VALUE OF RECTANGULAR TENSORS

Authors

  • Nur Fadhilah Ibrahim School of Informatics and Applied Mathematics, Universiti Malaysia Terengganu, 21030 Kuala Terengganu, Malaysia
  • Nurul Akmal Mohamed Mathematics Department, Faculty of Science and Mathematics, 35900 Universiti Pendidikan Sultan Idris, Proton City, Tanjung Malim, Perak, Malaysia

DOI:

https://doi.org/10.11113/jt.v78.9005

Keywords:

Rectangular tensor, iterative method, singular value, convergence

Abstract

The applications of real rectangular tensors, among others, including the strong ellipticity condition problem within solid mechanics, and the entanglement problem within quantum physics. A method was suggested by Zhou, Caccetta and Qi in 2013, as a means of calculating the largest singular value of a nonnegative rectangular tensor. In this paper, we show that the method converges under weak irreducibility condition, and that it has a Q-linear convergence.   

References

Knowles, J. K. and Sternberg, E. 1975. On The Ellipticity of The Equations of Nonlinear Elastostatics for A Specialmaterial. J. Elasticity. 5: 341-361.

Knowles, J. K. and Sternberg, E. 1977. On The Failure of Ellipticity of The Equations for Finite Elastostatic Plane Strain. Arch. Ration. Mech. Anal. 63: 321-336.

Rosakis, P. 1990. Ellipticity and Deformations with Discontinuous Deformation Gradients in Finite Elastostatics. Arch. Ration. Mech. Anal. 109: 1-37.

Wang, Y. and Aron, M. 1996. A Reformulation of The Strong Ellipticity Conditions for Unconstrained Hyperelasticmedia. J. Elasticity. 44: 89-96.

Dahl, D., Leinass, J. M. Myrheim, J. and Ovrum, E. 2007. A Tensor Product Matrix Approximation Problem in Quantum Physics. Linear Algebra Appl. 420: 711-725.

Einstein, A., Podolsky, B. and Rosen, N. 1935. Can Quantum-Mechanical Description of Physical Reality be Considered Complete? Phys. Rev. 47: 777-780.

Chang, K., Qi, L. and Zhou, G. 2010. Singular Values of a Real Rectangular Tensor. Journal of Mathematical Analysis and Applications. 370: 284-294.

Wood, R. J. and O'Neill, M. J. 2007. Finding The Spectral Radius of A Large Sparse Non-Negative Matrix. ANZIAM J. 48: C330-C345.

Wood, R. J. and O'Neill, M. J. 2007. An Always Convergent Method for Finding The Spectral Radius of An Irreducible Non-Negative Matrix. ANZIAM J. 45: C474-C485.

Ng, M., Qi, L. and Zhou, G. 2009. Finding The Largest Eigenvalue of A Nonnegative Tensor. SIAM J. Matrix Anal. Appl. 31: 1090-1099.

Zhou, G., Caccetta, L. and Qi, L. 2013. Convergence of An Algorithm for The Largest Singular Value of A Nonnegative Rectangular Tensor. Linear Algebra and its Applications. 438: 959-968.

Jordehi, A.R. 2015. Enhanced Leader PSO (ELPSO): A New PSO Variant for Solving Global Optimisation Problems. Applied Soft Computing. 26: 401-417.

Jordehi, A. R., Jasni, J., Wahab, N. A., Kadir M. Z., and Javadi, M. S. 2015. Enhanced Leader PSO (ELPSO): A New Algorithm for Allocating Distributed TCSC’s in Power Systems. International Journal of Electrical Power & Energy Systems. 64: 771-784.

Jordehi, A.R. 2015. Brainstorm Optimisation Algorithm (BSOA): An Efficient Algorithm for Finding Optimal Location and Setting of FACTS Devices in Electric Power Systems. International Journal of Electrical Power & Energy Systems. 69: 48-57.

Jordehi, A. R. 2014. A Chaotic-Based Big Bang-Big Crunch Algorithm For Solving Global Optimisation Problems. Neural Computing and Applications. 25: 1329-1335.

Jordehi, A. R. 2015. Chaotic Bat Swarm Optimisation (CBSO). Applied Soft Computing. 26: 523-530.

Varga, R. 1965. Matrix Iterative Analysis. Englewood Cliffs, New Jersey: Prentice-Hall, Inc.,

Minc, H. 1988. Nonnegative Matrices. New York: John Wiley and Sons.

Golub, G. H. and Loan, C. F. V. 1996. Matrix Computations. Baltimore: Johns Hopkins University Press.

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

Friedland, S., Gaubert, S. and Han, L. 2011. Perron-Frobenius Theorem for Nonnegative Multilinear Forms and Extensions. Linear Algebra Appl. 438: 738-749.

Zhou, G., Qi, L., and Wu, S. 2013. Efficient Algorithms for Computing The Largest Eigenvalue of A Nonnegative Tensor. Front. Math. China. 8: 155-168.

Zhang, L. 2013. Linear Convergence of An Algorithm for Largest Singular Value of A Nonnegative Rectangular Tensor. Front. Math. China. 8: 141-153.

Ibrahim, N. F. 2014. An Algorithm for The Largest Eigenvalue of Nonhomogeneous Nonnegative Polynomials. Numerical Algebra, Control and Optimization. 4: 75-91.

Downloads

Published

2016-06-13

Issue

Section

Science and Engineering

How to Cite

THE RATE OF CONVERGENCE AND WEAKER CONVERGENT CONDITION FOR THE METHOD FOR FINDING THE LARGEST SINGULAR VALUE OF RECTANGULAR TENSORS. (2016). Jurnal Teknologi (Sciences & Engineering), 78(6-5). https://doi.org/10.11113/jt.v78.9005