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Regularization Methods for Ill-posed Problems

Neuman, Arthur James, III
http://rave.ohiolink.edu/etdc/view?acc_num=kent1273611079

Abstract Details

2010, MS, Kent State University, College of Arts and Sciences / Department of Mathematical Sciences.
This thesis examines solution methods for large linear systems of equations with a matrix of ill-determined rank and an error-contaminated right-hand side. The numerical solution is delicate, because the matrix is very ill-conditioned and may be singular. To solve such systems, one replaces the system with one that is less sensitive to error a process known as regularization. This thesis focuses on the regularization method known as truncated iteration. A new algorithm is presented and compared to other existing methods.
Lothar Reichel, PhD (Advisor)
M. Kazim Khan, PhD (Committee Member)
Jing Li, PhD (Committee Member)
28 p.
Mathematics
Regularization methods; iterative methods; range restricted GMRES; RRGMRES; krylov subspace method

Recommended Citations

Citations

  • Neuman, III, A. J. (2010). Regularization Methods for Ill-posed Problems [Master's thesis, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1273611079

    APA Style (7th edition)

  • Neuman, III, Arthur. Regularization Methods for Ill-posed Problems. 2010. Kent State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1273611079.

    MLA Style (8th edition)

  • Neuman, III, Arthur. "Regularization Methods for Ill-posed Problems." Master's thesis, Kent State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=kent1273611079

    Chicago Manual of Style (17th edition)

kent1273611079
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This open access ETD is published by Kent State University and OhioLINK.