Convergence of Generalized Relaxed SSOR Method for Augmented Systems

Li Tao Zhang; Shao Hua Cheng; Ting Zhu Huang; Tong Xiang Gu

doi:10.4028/www.scientific.net/AMM.29-32.2563

Paper Titles

Study on Emergency Evacuation Ability of Exits in Public Assembly Places
p.2540

Simulation and Verification on Motorcycle Ride Comfort under Pulse Road
p.2544

Experimental Study of Stress-Generated Potentials on Large Cattle Femur under Simulated Physiological Loading State
p.2549

Investigation of the Disk Cavitator Cavitating Flow Characteristics under Relatively High Cavitation Number
p.2555

Convergence of Generalized Relaxed SSOR Method for Augmented Systems
p.2563

Analysis of Influence Factors on Heavy Metal Release from Mine Waste Rock in Fu Xin Mine Area
p.2570

A Modified Gene Optimization for TSP
p.2576

Multiparty Quantum Determined Key Distribution Protocol Using Open-Destination Teleportation
p.2580

Algorithm for Automatic 3-D Scanned Bullet Identification Based on the Principle of Human Vision
p.2585

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 29-32Convergence of Generalized Relaxed SSOR Method for...

Convergence of Generalized Relaxed SSOR Method for Augmented Systems

Abstract:

In this paper, we present the generalized relaxed SSOR method (GRSSOR) for solving the large sparse augmented systems of linear equations, which is the extension of SOR-like, GSOR and GSSOR methods. Furthermore, convergence of GRSSOR method for augmented systems is analyzed, which show that GRSSOR method with appropriate parameters will have very good effectiveness

You might also be interested in these eBooks

Applied Mechanics And Mechanical Engineering

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 29-32)

Pages:

2563-2569

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.29-32.2563

Citation:

Cite this paper

Online since:

August 2010

Authors:

Li Tao Zhang, Shao Hua Cheng, Ting Zhu Huang, Tong Xiang Gu

Keywords:

Augmented Systems, Convergence, Generalized Relaxed SSOR Method

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Z. Z. Bai, B. N. Parlett and Z. Q. Wang, On generalized successive overrelaxation methods for augmented linear systems, Numer. Math., 2005, pp.1-38.

DOI: 10.1007/s00211-005-0643-0

Google Scholar

[2] M. T. Darvishi and P. Hessari, Symmetric SOR method for augmented systems, Appl. Math. Comput, 2006, pp.409-415.

DOI: 10.1016/j.amc.2006.05.094

Google Scholar

[3] H. Elman and D. Silvester, Fast nonsymmetric iterations and preconditioning for Navier-Stokes equations, SIAM J. Sci. Comput., 1996, pp.33-46.

DOI: 10.1137/0917004

Google Scholar

[4] B. Fischer, A. Ramage, D. J. Silvester and A. J. Wathen, Minimum residual methods for augmented systems, BIT, 1998, pp.527-543.

DOI: 10.1007/bf02510258

Google Scholar

[5] G. H. Golub, X. Wu and J. Y. Yuan, SOR-like methods for augmented systems, BIT, 2001, pp.71-85.

Google Scholar

[6] C. H. Santos, B. P. B. Silva and J. Y. Yuan, Block SOR methods for rank deficient least squares problems, J. Comput. Appl. Math., 1998, pp.1-9.

DOI: 10.1016/s0377-0427(98)00114-9

Google Scholar

[7] S. Wright, Stability ofaugm ented system factorizations in interior-point methods, SIAM J. Matrix Anal. Appl., 1997, pp.191-222.

DOI: 10.1137/s0895479894271093

Google Scholar

[8] D. M. Young, Iteratin Solution for Large Systems, Academic Press, New York, (1971).

Google Scholar

[9] J. Y. Yuan, Numerical methods for generalized least squares problems, J. Comput. Appl. Math., 1996, pp.571-584.

Google Scholar

[10] J. Y. Yuan and A. N. Iusem, Preconditioned conjugate gradient method for generalized least squares problems, J. Comput. Appl. Math., 1996, pp.287-297.

DOI: 10.1016/0377-0427(95)00239-1

Google Scholar

[11] G. F. Zhang and Q. H. Lu, On generelized symmetric SOR method for augmented systems, J. Comput. Appl. Math., 2008, pp.51-58.

Google Scholar