Robust Approximate Cholesky Factorization of Rank-Structured Symmetric Positive Definite Matrices

Given a symmetric positive definite matrix A, we compute a structured approximate Cholesky factorization A [asymptotically =] R^T R up to any desired accuracy, where R is an upper triangular hierarchically semiseparable (HSS) matrix. The factorization is stable, robust, and efficient. The method com...

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Bibliographic Details
Published in:	SIAM journal on matrix analysis and applications Vol. 31; no. 5; pp. 2899 - 2920
Main Authors:	Xia, Jianlin, Gu, Ming
Format:	Journal Article
Language:	English
Published:	Philadelphia, PA Society for Industrial and Applied Mathematics 01.01.2010
Subjects:	Algebra Algorithms Approximation Breaking down Cholesky factorization Complement Compressing Exact sciences and technology Factorization Linear and multilinear algebra, matrix theory Mathematical analysis Mathematical models Mathematics Matrix Numerical analysis Numerical analysis. Scientific computation Numerical linear algebra Sciences and techniques of general use Studies Triangular matrix Compression Stabilization Schur compensation Numerical data Cholesky method Compensation 65F30 Development Sparse matrix hierarchically semiseparable structure Schur complement Approximation off-diagonal compression robust preconditioner Rank Algorithm Factorization Numerical analysis Symmetric matrix 15A12 Linear algebra Positive definite matrix Potential method Performance Preconditioning 65F05
ISSN:	0895-4798, 1095-7162
Online Access:	Get full text
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