Hilbert Space Splittings And Iterative Methods

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Hilbert Space Splittings and Iterative Methods

Hilbert Space Splittings and Iterative Methods
Author :
Publisher : Springer Nature
Total Pages : 444
Release :
ISBN-10 : 9783031743702
ISBN-13 : 3031743709
Rating : 4/5 (709 Downloads)

Book Synopsis Hilbert Space Splittings and Iterative Methods by : Michael Griebel

Download or read book Hilbert Space Splittings and Iterative Methods written by Michael Griebel and published by Springer Nature. This book was released on 2024 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about the theory of so-called Schwarz methods for solving variational problems in a Hilbert space V arising from linear equations and their associated quadratic minimization problems. Schwarz methods are based on the construction of a sequence of approximate solutions by solving auxiliary variational problems on a set of (smaller, finite-dimensional) Hilbert spaces Vi in a certain order, combining them, and using the combined approximations in an iterative procedure. The spaces Vi form a so-called space splitting for V, they need not necessarily be subspaces of V, and their number can be finite or infinite. The convergence behavior of Schwarz methods is influenced by certain properties of the space splittings they are based on. These properties are identified, and a detailed treatment of traditional deterministic and more recent greedy and stochastic orderings in the subproblem solution process is given, together with an investigation of accelerated methods. To illustrate the abstract theory, the numerical linear algebra analogs of the iterative methods covered in the book are discussed. Its standard application to the convergence theory of multilevel and domain decomposition methods for solving PDE problems is explained, and links to optimization theory and online learning algorithms are given. Providing an introduction and overview of iterative methods which are based on problem decompositions and suitable for parallel and distributed computing, the book could serve as the basis for a one- or two-semester course for M.S. and Ph.D. students specializing in numerical analysis and scientific computing. It will also appeal to a wide range of researchers interested in scientific computing in the broadest sense.


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