04173nam a22004575i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001200172072001700184072002300201072001600224100008600240245011100326250001800437264006900455300005200524336002600576337002600602338003600628347002400664490006700688505068600755520175501441650004103196650006103237700008303298710003403381773002603415776003603441776003603477776003603513830007403549856004603623912001403669912001503683999001703698978-3-031-74370-2DE-He21320251030113301.0cr nn 008mamaa241107s2024    sz |    s    |||| 0|eng d  a97830317437029978-3-031-74370-27 a10.1007/978-3-031-74370-22doi 4aQA71-90 7aPBKS2bicssc 7aMAT0410002bisacsh 7aPBKS2thema1 aGriebel, Michael.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut98714310aHilbert Space Splittings and Iterative Methodsh[electronic resource] /cby Michael Griebel, Peter Oswald.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aIX, 440 p. 1 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aSpringer Series in Computational Mathematics,x2198-3712 ;v620 a1 Introduction -- 2 Hilbert space splittings: Abstract theory -- References -- 3 Hilbert space splittings: Examples and extensions -- References -- 4 Schwarz iterative methods: Finite Omega -- References -- 5 Special topics and extensions -- References -- 6 Schwarz approximation methods: Infinite Omega -- References -- 7 Applications to PDE solvers -- References -- A Hilbert space basics -- A.1 Spaces: Basic notation, definitions and properties -- A.2 Operators between Hilbert spaces -- A.3 Linear equations and variational problems -- A.4 Constructions on Hilbert spaces -- A.5 Sobolev spaces on domains -- A.6 Reproducing kernel Hilbert spaces (RKHS) -- References -- Index.  aThis 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. 0aMathematicsxData processing.96571514aComputational Mathematics and Numerical Analysis.9660731 aOswald, Peter.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut9871442 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303174369608iPrinted edition:z978303174371908iPrinted edition:z9783031743726 0aSpringer Series in Computational Mathematics,x2198-3712 ;v6298714540uhttps://doi.org/10.1007/978-3-031-74370-2  aZDB-2-SMA  aZDB-2-SXMS  c64773d64773