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＜電子ブック＞
Sparse Grids and Applications - Munich 2012 / edited by Jochen Garcke, Dirk Pflüger
(Lecture Notes in Computational Science and Engineering. ISSN:21977100 ; 97)

版	1st ed. 2014.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2014
本文言語	英語
大きさ	VIII, 344 p. 106 illus., 72 illus. in color : online resource
著者標目	Garcke, Jochen editor Pflüger, Dirk editor SpringerLink (Online service)
件　名	LCSH:Mathematics -- Data processing  全ての件名で検索 FREE:Computational Mathematics and Numerical Analysis FREE:Computational Science and Engineering
一般注記	Gerrit Buse, Dirk Pfl¨uger, and Riko Jacob: Efficient Pseudorecursive Evaluation Schemes for Non-Adaptive Sparse Grids -- Oliver G. Ernst and Bj¨orn Sprungk: Stochastic Collocation for Elliptic PDEs with Random Data – The Lognormal Case -- Michael Griebel and Helmut Harbrecht: On the Convergence of the Combination Technique -- Michael Griebel and Jan Hamaekers: Fast Discrete Fourier Transform on Generalized Sparse Grids -- Michael Griebel and Jens Oettershagen: Dimension-adaptive Sparse Grid Quadrature for Integrals with Boundary Singularities -- Max Gunzburger, Clayton G. Webster, and Guannan Zhang: An Adaptive Wavelet Stochastic Collocation Method for Irregular Solutions of Partial Differential Equations with Random Input Data -- Brendan Harding and Markus Hegland: Robust Solutions to PDEs with Multiple Grids -- Riko Jacob: Efficient Regular Sparse Grid Hierarchization by a Dynamic Memory Layout -- Valeriy Khakhutskyy and Dirk Pflüger: Alternating Direction Method of Multipliers for Hierarchical Basis Approximators -- Christoph Kowitz and Markus Hegland: An Opticom Method for Computing Eigenpairs -- Benjamin Peherstorfer, Fabian Franzelin, Dirk Pfl¨uger, and Hans-Joachim Bungartz: Classification with Probability Density Estimation on Sparse Grids -- Bettina Schieche and Jens Lang: Adjoint Error Estimation for Stochastic CollocationMethods -- Sebastian Ullmann and Jens Lang: POD-Galerkin Modeling and Sparse-Grid Collocation for a Natural Convection Problem with Stochastic Boundary Conditions -- Matthias Wong and Markus Hegland: Opticom and the Iterative Combination Technique for Convex Minimisation.   Sparse grids have gained increasing interest in recent years for the numerical treatment of high-dimensional problems. Whereas classical numerical discretization schemes fail in more than three or four dimensions, sparse grids make it possible to overcome the “curse” of dimensionality to some degree, extending the number of dimensions that can be dealt with. This volume of LNCSE collects the papers from the proceedings of the second workshop on sparse grids and applications, demonstrating once again the importance of this numerical discretization scheme. The selected articles present recent advances on the numerical analysis of sparse grids as well as efficient data structures, and the range of applications extends to uncertainty quantification settings and clustering, to name but a few examples HTTP:URL=https://doi.org/10.1007/978-3-319-04537-5

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