| 000 | 03502nam a22005535i 4500 | ||
|---|---|---|---|
| 001 | 978-3-031-25820-6 | ||
| 003 | DE-He213 | ||
| 005 | 20240508090327.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 230429s2023 sz | s |||| 0|eng d | ||
| 020 |
_a9783031258206 _9978-3-031-25820-6 |
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| 024 | 7 |
_a10.1007/978-3-031-25820-6 _2doi |
|
| 050 | 4 | _aQA297-299.4 | |
| 072 | 7 |
_aPBKS _2bicssc |
|
| 072 | 7 |
_aMAT041000 _2bisacsh |
|
| 072 | 7 |
_aPBKS _2thema |
|
| 082 | 0 | 4 |
_a518 _223 |
| 100 | 1 |
_aScott, Jennifer. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
| 245 | 1 | 0 |
_aAlgorithms for Sparse Linear Systems _h[electronic resource] / _cby Jennifer Scott, Miroslav Tůma. |
| 250 | _a1st ed. 2023. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Birkhäuser, _c2023. |
|
| 300 |
_aXIX, 242 p. 70 illus., 27 illus. in color. _bonline resource. |
||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
||
| 490 | 1 |
_aNečas Center Series, _x2523-3351 |
|
| 505 | 0 | _aAn introduction to sparse matrices -- Sparse matrices and their graphs -- Introduction to matrix factorizations -- Sparse Cholesky sovler: The symbolic phase -- Sparse Cholesky solver: The factorization phase -- Sparse LU factorizations -- Stability, ill-conditioning and symmetric indefinite factorizations -- Sparse matrix ordering algorithms -- Algebraic preconditioning and approximate factorizations -- Incomplete factorizations -- Sparse approximate inverse preconditioners. | |
| 506 | 0 | _aOpen Access | |
| 520 | _aLarge sparse linear systems of equations are ubiquitous in science, engineering and beyond. This open access monograph focuses on factorization algorithms for solving such systems. It presents classical techniques for complete factorizations that are used in sparse direct methods and discusses the computation of approximate direct and inverse factorizations that are key to constructing general-purpose algebraic preconditioners for iterative solvers. A unified framework is used that emphasizes the underlying sparsity structures and highlights the importance of understanding sparse direct methods when developing algebraic preconditioners. Theoretical results are complemented by sparse matrix algorithm outlines. This monograph is aimed at students of applied mathematics and scientific computing, as well as computational scientists and software developers who are interested in understanding the theory and algorithms needed to tackle sparsesystems. It is assumed that the reader has completed a basic course in linear algebra and numerical mathematics. . | ||
| 650 | 0 | _aNumerical analysis. | |
| 650 | 0 | _aAlgebras, Linear. | |
| 650 | 0 |
_aMathematics _xData processing. |
|
| 650 | 1 | 4 | _aNumerical Analysis. |
| 650 | 2 | 4 | _aLinear Algebra. |
| 650 | 2 | 4 | _aComputational Science and Engineering. |
| 700 | 1 |
_aTůma, Miroslav. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031258190 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031258213 |
| 830 | 0 |
_aNečas Center Series, _x2523-3351 |
|
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-25820-6 |
| 912 | _aZDB-2-SMA | ||
| 912 | _aZDB-2-SXMS | ||
| 912 | _aZDB-2-SOB | ||
| 999 |
_c37772 _d37772 |
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