Summary

Proceedings of the 2012 International Symposium on Nonlinear Theory and its Applications

2012

Session Number:D2L-D

Session:

Number:876

Backward Error Bounds of Block LDLT factorizations

Takeshi Ogita,  

pp.876-876

Publication Date:

Online ISSN:2188-5079

DOI:10.15248/proc.1.876

PDF download (253.6KB)

Summary:
To solve linear systems is ubiquitous since it is one of the basic and significant tasks in scientific computing. Floating-point arithmetic is widely used for this purpose. Since it uses finite precision arithmetic and numbers, rounding errors are included in computed results.
Matrix factorizations such as LU and Cholesky factorizations are used for solving linear systems. In particular, block LDLT factorizations apply to symmetric and indefinite matrices. In this talk backward error bounds on block LDLT factorizations by floating-point arithmetic are given. The error bounds are computable and easy to calculate normwise.

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