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Judul Algorithms for Sparse Linear Systems / Jennifer Scott ; Miroslav Tuma
Pengarang Scott, Jennifer
Tuma, Miroslav
Penerbitan Cham : Springer Nature, 2023
Deskripsi Fisik 242 p. :ilus.
ISBN 9783031258206
Subjek NUMERICAL ANALYSIS
ALGEBRA
MATHS FOR SCIENTISTS
Catatan Large 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 lin
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Lokasi Akses Online https://library.oapen.org/handle/20.500.12657/62987

 
No Barcode No. Panggil Akses Lokasi Ketersediaan
267425192 512.9 Alg Baca Online Perpustakaan Pusat - Online Resources
Ebook
Tersedia
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100 1 # $a Scott, Jennifer
245 1 # $a Algorithms for Sparse Linear Systems /$c Jennifer Scott ; Miroslav Tuma
260 # # $a Cham :$b Springer Nature,$c 2023
300 # # $a 242 p. : $b ilus.
505 # # $a Large 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.
650 # # $a ALGEBRA
650 # # $a MATHS FOR SCIENTISTS
650 # # $a NUMERICAL ANALYSIS
700 1 # $a Tuma, Miroslav
856 # # $a https://library.oapen.org/handle/20.500.12657/62987
990 # # $a 267425192
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