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Numerical and Symbolic Scientific Computing [electronic resource] : Progress and Prospects / edited by Ulrich Langer, Peter Paule.

By: Langer, Ulrich [editor.].
Contributor(s): Paule, Peter [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Texts & Monographs in Symbolic Computation, A Series of the Research Institute for Symbolic Computation, Johannes Kepler University, Linz, Austria: Publisher: Vienna : Springer Vienna : Imprint: Springer, 2012Description: VIII, 358 p. 50 illus., 13 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783709107942.Subject(s): Mathematics | Algebra | Computer science -- Mathematics | Engineering mathematics | Mathematics | Computational Mathematics and Numerical Analysis | Algebra | Appl.Mathematics/Computational Methods of EngineeringDDC classification: 518 | 518 Online resources: Click here to access online In: Springer eBooksSummary: The book presents the state of the art, new results, and it also includes articles pointing to future developments. Most of the articles center around the theme of partial differential equations. Major aspects are fast solvers in elastoplasticity, symbolic analysis for boundary problems, symbolic treatment of operators, computer algebra, and finite element methods, a symbolic approach to finite difference schemes, cylindrical algebraic decomposition and local Fourier analysis, and white noise analysis for stochastic partial differential equations. Further numerical-symbolic topics range from applied and computational geometry to computer algebra methods used for total variation energy minimization.
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The book presents the state of the art, new results, and it also includes articles pointing to future developments. Most of the articles center around the theme of partial differential equations. Major aspects are fast solvers in elastoplasticity, symbolic analysis for boundary problems, symbolic treatment of operators, computer algebra, and finite element methods, a symbolic approach to finite difference schemes, cylindrical algebraic decomposition and local Fourier analysis, and white noise analysis for stochastic partial differential equations. Further numerical-symbolic topics range from applied and computational geometry to computer algebra methods used for total variation energy minimization.

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