{"product_id":"9783031743696","title":"Springer Series in Computational Mathematics","description":"\u003ch1\u003eSpringer Series in Computational Mathematics\u003c\/h1\u003e \u003ch2\u003eGriebel, Michael; Oswald, Peter\u003c\/h2\u003e \u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis book is about the theory of so-called Schwarz methods for solving variational problems in a Hilbert space \u003cem\u003eV\u003c\/em\u003e 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 $V_i$ in a certain order, combining them, and using the combined approximations in an iterative procedure. The spaces $V_i$ form a so-called space splitting for \u003cem\u003eV\u003c\/em\u003e, they need not necessarily be subspaces of \u003cem\u003eV\u003c\/em\u003e,\u003cem\u003e \u003c\/em\u003eand their number can be finite or infinite.\u003c\/p\u003e\n\n\u003cp\u003eThe 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.\u003c\/p\u003e\n\n\u003cp\u003eProviding 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.\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2024-11-07\u003c\/p\u003e \u003cp\u003eFormat: Hardcover\u003c\/p\u003e \u003cp\u003eISBN-13: 9783031743696\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-3-031-74370-2\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 440\u003c\/p\u003e ","brand":"Springer Nature Switzerland","offers":[{"title":"Default Title","offer_id":44398584594572,"sku":"9783031743696","price":143.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783031743696.jpg?v=1775733228","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9783031743696","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}