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Sparse grids and applications = Stut...

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Sparse grids and applications = Stuttgart 2014 /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Sparse grids and applications/ edited by Jochen Garcke, Dirk Pfluger.
其他題名:	Stuttgart 2014 /
其他作者:	Garcke, Jochen.
出版者:	Cham :Springer International Publishing : : 2016.,
面頁冊數:	viii, 336 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Sparse matrices - Congresses. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-28262-6
ISBN:	9783319282626

Sparse grids and applications = Stuttgart 2014 /
Sparse grids and applicationsStuttgart 2014 /[electronic resource] :edited by Jochen Garcke, Dirk Pfluger. - Cham :Springer International Publishing :2016. - viii, 336 p. :ill., digital ;24 cm. - Lecture notes in computational science and engineering,1091439-7358 ;. - Lecture notes in computational science and engineering ;52..

This volume of LNCSE is a collection of the papers from the proceedings of the third workshop on sparse grids and applications. Sparse grids are a popular approach for the numerical treatment of high-dimensional problems. Where classical numerical discretization schemes fail in more than three or four dimensions, sparse grids, in their different guises, are frequently the method of choice, be it spatially adaptive in the hierarchical basis or via the dimensionally adaptive combination technique. 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. The book also discusses a range of applications, including uncertainty quantification and plasma physics.

ISBN: 9783319282626

Standard No.: 10.1007/978-3-319-28262-6doiSubjects--Topical Terms:

1072530
Sparse matrices
--Congresses.

LC Class. No.: QA188

Dewey Class. No.: 004.36

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520 $a This volume of LNCSE is a collection of the papers from the proceedings of the third workshop on sparse grids and applications. Sparse grids are a popular approach for the numerical treatment of high-dimensional problems. Where classical numerical discretization schemes fail in more than three or four dimensions, sparse grids, in their different guises, are frequently the method of choice, be it spatially adaptive in the hierarchical basis or via the dimensionally adaptive combination technique. 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. The book also discusses a range of applications, including uncertainty quantification and plasma physics.
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