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

Por: Colaborador(es): Tipo de material: TextoTextoSeries Texts & Monographs in Symbolic Computation, A Series of the Research Institute for Symbolic Computation, Johannes Kepler University, Linz, AustriaEditor: Vienna : Springer Vienna : Imprint: Springer, 2012Descripción: viii, 358 páginas 50 ilustraciones, 13 ilustraciones en color. recurso en líneaTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de portador:
  • recurso en línea
ISBN:
  • 9783709107942
Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:
  • QA71-90
Recursos en línea: Resumen: 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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