Numerical and symbolic scientific computing: progress and prospects
(eBook)
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.
Langer, U., & Paule, P. (2012). Numerical and symbolic scientific computing: progress and prospects. Vienna ; New York, SpringerWienNew York.
Chicago / Turabian - Author Date Citation (style guide)Langer, Ulrich, 1952- and Peter. Paule. 2012. Numerical and Symbolic Scientific Computing: Progress and Prospects. Vienna ; New York, SpringerWienNew York.
Chicago / Turabian - Humanities Citation (style guide)Langer, Ulrich, 1952- and Peter. Paule, Numerical and Symbolic Scientific Computing: Progress and Prospects. Vienna ; New York, SpringerWienNew York, 2012.
MLA Citation (style guide)Langer, Ulrich and Peter Paule. Numerical and Symbolic Scientific Computing: Progress and Prospects. Vienna ; New York, SpringerWienNew York, 2012.
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245 | 0 | 0 | |a Numerical and symbolic scientific computing :|b progress and prospects /|c Ulrich Langer, Peter Paule, editors. |
260 | |a Vienna ;|a New York :|b SpringerWienNew York,|c ©2012. | ||
264 | 1 | |a Vienna ;|a New York :|b SpringerWienNew York,|c [2012] | |
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505 | 0 | |a Approximate implicitization of space curves / Martin Aigner, Bert Jüttler, and Adrien Poteaux -- Sparsity optimized high order finite element functions on simplices / Sven Beuchler, Veronika Pillwein, Joachim Schöberl, and Sabine Zaglmayr -- Fast solvers and a posteriori error estimates in elastoplasticity / Peter G. Gruber, Johanna Kienesberger, Ulrich Langer, Joachim Schöberl, and Jan Valdman -- A symbolic-numeric algorithm for genus computation / Mădălina Hodorog and Josef Schicho -- The "Seven Dwarfs" of symbolic computation / Erich L. Kaltofen -- Computer algebra meets finite elements: an efficient implementation for Maxwell's equations / Victor Levandovskyy and Bernd Martin -- White noise analysis for stochastic partial differential equations / Hermann G. Matthies -- Smoothing analysis of an all-at-once multigrid approach for optimal control problems using symbolic computation / Stefan Takacs and Veronika Pillwein -- Analytical evaluations of double integral expressions related to total variation / Carsten Pontow and Otmar Scherzer -- Sound and complete verification condition generator for functional recursive programs / Nikolaj Popov and Tudor Jebelean -- An introduction to automated delivery in geometry through symbolic computation / Tomas Recio and María P. Vélez -- Symbolic analysis for boundary problems: from rewriting to parametrized Gröbner bases / Markus Rosenkranz, Georg Regensburger, Loredana Tec, and Bruno Buchberger -- Linear partial differential equations and linear partial differential operators in computer algebra / Ekaterina Shemyakova and Franz Winkler. | |
520 | |a 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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