Stability and sensitivity of tridiagonal LU factorization without pivoting
نویسنده
چکیده
In this paper the accuracy of LU factorization of tridiagonal matrices without pivoting is considered. Two types of componentwise condition numbers for the L and U factors of tridiadonal matrices are presented and compared. One type is a condition number with respect to small relative perturbations of each entry of the matrix. The other type is a condition number with respect to small componentwise perturbations of the kind appearing in the backward error analysis of the usual algorithm for the LU factorization. We show that both condition numbers are of similar magnitude. This means that the algorithm is componentwise forward stable, i.e., the forward errors are of similar magnitude to those produced by a componentwise backward stable method. Moreover the presented condition numbers can be computed in O(n) flops, which allows to estimate with low cost the forward errors. AMS subject classification: 65F35, 65F50, 15A12, 15A23, 65G50.
منابع مشابه
Stability of Block LDLT Factorization of a Symmetric Tridiagonal Matrix
For symmetric indeenite tridiagonal matrices, block LDL T factorization without interchanges is shown to have excellent numerical stability when a pivoting strategy of Bunch is used to choose the dimension (1 or 2) of the pivots.
متن کاملStability of block LDL factorization of a symmetric tridiagonal matrix
For symmetric inde®nite tridiagonal matrices, block LDL factorization without interchanges is shown to have excellent numerical stability when a pivoting strategy of Bunch is used to choose the dimension (1 or 2) of the pivots. Ó 1999 Elsevier Science Inc. All rights reserved. AMS classi®cation: 65F05; 65G05
متن کاملLU factorization with panel rank revealing pivoting and its communication avoiding version
We present the LU decomposition with panel rank revealing pivoting (LU PRRP), an LU factorization algorithm based on strong rank revealing QR panel factorization. LU PRRP is more stable than Gaussian elimination with partial pivoting (GEPP), with a theoretical upper bound of the growth factor of (1+ τb) n b , where b is the size of the panel used during the block factorization, τ is a parameter...
متن کاملStable Factorizations of Symmetric Tridiagonal and Triadic Matrices
We call a matrix triadic if it has no more than two nonzero off-diagonal elements in any column. A symmetric tridiagonal matrix is a special case. In this paper we consider LXLT factorizations of symmetric triadic matrices, where L is unit lower triangular and X is diagonal, block diagonal with 1×1 and 2×2 blocks, or the identity with L lower triangular. We prove that with diagonal pivoting, th...
متن کاملCalculs pour les matrices denses : coût de communication et stabilité numérique. (Dense matrix computations : communication cost and numerical stability)
This dissertation focuses on a widely used linear algebra kernel to solve linear systems, that is the LU decomposition. Usually, to perform such a computation one uses the Gaussian elimination with partial pivoting (GEPP). The backward stability of GEPP depends on a quantity which is referred to as the growth factor, it is known that in general GEPP leads to modest element growth in practice. H...
متن کامل