001463067 000__ 03656cam\a22005897i\4500
001463067 001__ 1463067
001463067 003__ OCoLC
001463067 005__ 20230601003304.0
001463067 006__ m\\\\\o\\d\\\\\\\\
001463067 007__ cr\cn\nnnunnun
001463067 008__ 230503s2023\\\\sz\a\\\\ob\\\\001\0\eng\d
001463067 020__ $$a9783031258206$$qelectronic book
001463067 020__ $$a3031258207$$qelectronic book
001463067 020__ $$z9783031258190
001463067 0247_ $$a10.1007/978-3-031-25820-6$$2doi
001463067 035__ $$aSP(OCoLC)1378155175
001463067 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX
001463067 049__ $$aISEA
001463067 050_4 $$aQA188$$b.S36 2023
001463067 08204 $$a512.9/434$$223/eng/20230503
001463067 1001_ $$aScott, Jennifer,$$eauthor.
001463067 24510 $$aAlgorithms for sparse linear systems /$$cJennifer Scott, Miroslav Tůma.
001463067 264_1 $$aCham :$$bBirkhäuser,$$c2023.
001463067 300__ $$a1 online resource (xix, 242 pages) :$$billustrations (some color).
001463067 336__ $$atext$$btxt$$2rdacontent
001463067 337__ $$acomputer$$bc$$2rdamedia
001463067 338__ $$aonline resource$$bcr$$2rdacarrier
001463067 4901_ $$aNečas Center series,$$x2523-3351
001463067 5050_ $$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.
001463067 5060_ $$aOpen access.$$5GW5XE
001463067 520__ $$aLarge sparse linear systems of equations are ubiquitous in science, engineering and beyond. This open access monograph focuses on factorization algorithms for solving such systems. It presents classical techniques for complete factorizations that are used in sparse direct methods and discusses the computation of approximate direct and inverse factorizations that are key to constructing general-purpose algebraic preconditioners for iterative solvers. A unified framework is used that emphasizes the underlying sparsity structures and highlights the importance of understanding sparse direct methods when developing algebraic preconditioners. Theoretical results are complemented by sparse matrix algorithm outlines. This monograph is aimed at students of applied mathematics and scientific computing, as well as computational scientists and software developers who are interested in understanding the theory and algorithms needed to tackle sparse systems. It is assumed that the reader has completed a basic course in linear algebra and numerical mathematics.
001463067 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed May 3, 2023).
001463067 650_0 $$aSparse matrices.
001463067 650_0 $$aLinear systems.
001463067 650_0 $$aAlgorithms.
001463067 655_0 $$aElectronic books.
001463067 7001_ $$aTuma, M.$$q(Miroslav),$$eauthor.
001463067 830_0 $$aNečas Center series,$$x2523-3351
001463067 852__ $$bebk
001463067 85640 $$3Springer Nature$$uhttps://link.springer.com/10.1007/978-3-031-25820-6$$zOnline Access$$91397441.2
001463067 909CO $$ooai:library.usi.edu:1463067$$pGLOBAL_SET
001463067 980__ $$aBIB
001463067 980__ $$aEBOOK
001463067 982__ $$aEbook
001463067 983__ $$aOnline
001463067 994__ $$a92$$bISE