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On the iterative refinement of the solution of ill-conditioned linear system of equations. (English) Zbl 1387.65030

Summary: Recently, D. K. Salkuyeh and A. Fahim [ibid. 88, No. 5, 950–956 (2011; Zbl 1220.65041)] have proposed a two-step iterative refinement of the solution of an ill-conditioned linear system of equations. In this paper, we first present a generalized two-step iterative refinement procedure to solve ill-conditioned linear system of equations and study its convergence properties. Afterward, it is shown that the idea of an orthogonal projection technique together with a basic stationary iterative method can be utilized to construct a new efficient and neat hybrid algorithm for solving the mentioned problem. The convergence of the offered hybrid approach is also established. Numerical examples are examined to demonstrate the feasibility of proposed algorithms and their superiority to some of existing approaches for solving ill-conditioned linear system of equations.

MSC:

65F10 Iterative numerical methods for linear systems

Citations:

Zbl 1220.65041
Full Text: DOI

References:

[1] O. Axelsson, Iterative Solution Methods, Cambridge University Press, Cambridge, 1996. · Zbl 0845.65011
[2] A. Frommer and D.B. Szyld, Weighted max norms, splittings, and overlapping additive Schwarz iterations, Numer. Math. 75(1) (1997), pp. 48-62. · Zbl 0934.65035
[3] P.C. Hansen, J.G. Nagy, and D.P. O’Leary, Deblurring Images: Matrices, Spectra, and Filtering, SIAM, Philadelphia, 2006. · Zbl 1112.68127
[4] Y. Kobayashi and T. Ogita, A fast and efficient algorithm for solving ill-conditioned linear systems, JSIAM Lett. 7 (2015), pp. 1-4. doi: 10.14495/jsiaml.7.1 · Zbl 07037333
[5] R.S. Martin, G. Peters, and J.H. Wilkinson, Symmetric decomposition of a positive definite matrix, Numer. Math. 7(5) (1965), pp. 362-383. doi: 10.1007/BF01436249 · Zbl 0135.37402
[6] R.S. Martin, G. Peters, and J.H. Wilkinson, Iterative refinement of the solution of a positive definite system of equations, Numer. Math. 8(3) (1966), pp. 203-216. doi: 10.1007/BF02162558 · Zbl 0158.33804
[7] J.M. Ortega, Numerical Analysis, A Second Course, Academic Press, New York, 1972. Reprinted by SIAM, Philadelphia, 1990. · Zbl 0248.65001
[8] S.M. Rump, Inversion of extremely ill-conditioned matrices in floating-point, Japan J. Indust. Appl. Math. 26(2-3) (2009), pp. 249-277. doi: 10.1007/BF03186534 · Zbl 1185.65050
[9] S.M. Rump, Accurate solution of dense linear systems, part I: Algorithms in rounding to nearest, J. Comput. Appl. Math 242 (2013), pp. 157-184. doi: 10.1016/j.cam.2012.10.010 · Zbl 1255.65084
[10] Y. Saad, Iterative Methods for Sparse Linear Systems, PWS Press, New York, 1995.
[11] Y. Saad and M.H. Schultz, GMRES: A generalized minimal residual algorithm for solving nonsymmetric linear systems, SIAM J. Sci. Stat. Comput. 7(3) (1986), pp. 856-869. doi: 10.1137/0907058 · Zbl 0599.65018
[12] D.K. Salkuyeh and A. Fahim, A new iterative refinement of the solution of ill-conditioned linear system of equations, Int. Comput. Math. 88(5) (2011), pp. 950-956. doi: 10.1080/00207161003713907 · Zbl 1220.65041
[13] R.S. Varga, Matrix Iterative Analysis, Prentice-Hall, Englewood Cliffs, NJ, 1962. · Zbl 0133.08602
[14] R.-P. Wen, G.-Y. Meng, and C.-L. Wang, Quasi-Chebyshev accelerated iteration methods based on optimization for linear systems, Comput. Math. Appl. 66(6) (2013), pp. 934-942. doi: 10.1016/j.camwa.2013.06.016 · Zbl 07863331
[15] X. Wu, R. Shao, and Y. Zhu, New iterative improvement of a solution for an ill-conditioned system of linear equations based on a linear dynamic system, Comput. Math. Appl. 44(8) (2002), pp. 1109-1116. doi: 10.1016/S0898-1221(02)00219-5 · Zbl 1035.65040
[16] M.K. Zak and F. Toutounian, A shifted nested splitting iterative method with applications to ill-posed problems and image restoration, Comput. Math. Appl. 71(1) (2016), pp. 213-223. doi: 10.1016/j.camwa.2015.11.005 · Zbl 1443.65048
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