Code: 43417915

Algorithms for Sparse Linear Systems

Name: Algorithms for Sparse Linear Systems
Brand: Springer Nature B.V.
SKU: 43417915
Price: 57.05 EUR
Availability: InStock
Author: Scott Jennifer Scott
ISBN: 9783031258213

by Scott Jennifer Scott, Tuma Miroslav Tuma

Language: English
Binding: Paperback
Number of pages: 264
Publisher: Springer Nature B.V., 2023
More about this

57.05 €

RRP: 57.06 €

You save 0.01 €

In stock at our supplier
Shipping in 10 - 18 days

Add to wishlist

7FATES: CHAKHO (novel)
25.83 € -29 %
Buy
MOS Study Guide for Microsoft Excel Expert Exam MO-201
20.26 € -24 %
Buy
101 More Drama Games and Activities
11.95 € -7 %
Buy
Beauty Is the Beast: Volume 1
8.71 € -10 %
Buy
Iterative Methods for Sparse Linear Systems
136.71 € -5 %
Pre-order
GUITAR ATLAS VOL 2 COMPLETE
72.65 €
Buy
Monster High POP! Vinyl Figure Skelita 9 cm
21.68 € -6 %
Buy
Helluva Boss Nendoroid Action Figure Blitzo 10 cm
77.82 €
Pre-order
Green Marketing
55.93 €
Buy
Greater Than a Tourist - Wadi Rum Jordan: 50 Travel Tips from a Local
16.41 € -10 %
Buy
Big Data
57.96 €
Buy
Hugh Wynne
19.45 € -25 %
Buy
Development Following Premature Birth
80.05 € -4 %
Buy
Grace of Being Fallible in Philosophy, Theology, and Religion
129 €
Buy

Give this book as a present today

Order book and choose Gift Order.
We will send you book gift voucher at once. You can give it out to anyone.
Book will be send to donee, nothing more to care about.

Book gift voucher sample Read more

More about Algorithms for Sparse Linear Systems

Book details
Synopsis
Trending among others

You get 138 loyalty points

Book synopsis

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.