A PRIORI CONVERGENCE OF THE GREEDY ALGORITHM FOR THE PARAMETRIZED REDUCED BASIS METHOD

被引:167
作者
Buffa, Annalisa [1 ]
Maday, Yvon [2 ,3 ]
Patera, Anthony T. [4 ]
Prud'homme, Christophe [5 ]
Turinici, Gabriel [6 ]
机构
[1] CNR, Inst Matemat Appl & Tecnol Informat, I-27100 Pavia, Italy
[2] Univ Paris 06, UPMC, Lab Jacques Louis Lions, UMR 7598, F-75005 Paris, France
[3] Brown Univ, Div Appl Math, Providence, RI 02912 USA
[4] MIT, Dept Mech Engn, Cambridge, MA 02139 USA
[5] Univ Grenoble 1 Joseph Fourier, Lab Jean Kuntzmann, F-38041 Grenoble 9, France
[6] Univ Paris 09, CEREMADE, F-75016 Paris, France
来源
ESAIM-MATHEMATICAL MODELLING AND NUMERICAL ANALYSIS-MODELISATION MATHEMATIQUE ET ANALYSE NUMERIQUE | 2012年 / 46卷 / 03期
关键词
Greedy algorithm; reduced basis approximations; a priori analysis; best fit analysis; PARTIAL-DIFFERENTIAL-EQUATIONS; POSTERIORI ERROR ESTIMATION; BASIS APPROXIMATION;
D O I
10.1051/m2an/2011056
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The convergence and efficiency of the reduced basis method used for the approximation of the solutions to a class of problems written as a parametrized PDE depends heavily on the choice of the elements that constitute the "reduced basis". The purpose of this paper is to analyze the a priori convergence for one of the approaches used for the selection of these elements, the greedy algorithm. Under natural hypothesis on the set of all solutions to the problem obtained when the parameter varies, we prove that three greedy algorithms converge; the last algorithm, based on the use of an a posteriori estimator, is the approach actually employed in the calculations.
引用
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页码:595 / 603
页数:9
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