Regularization without preliminary knowledge of smoothness and error behaviour

被引:19
作者
Bauer, F
Pereverzev, S
机构
[1] Univ Gottingen, Inst Numerical & Appl Math, D-37083 Gottingen, Germany
[2] Austrian Acad Sci, RICAM, A-4040 Linz, Austria
关键词
D O I
10.1017/S0956792505006236
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The mathematical formulation of many physical problems results in the task of inverting a compact operator. The only known sensible solution technique is regularization which poses a severe problem in itself. Classically one dealt with deterministic noise models and required the knowledge of smoothness of the solution or the overall error behaviour. We will show that we can guarantee an asymptotically almost optimal regularization for a physically motivated noise model under no assumptions for the smoothness and rather weak assumptions on the noise behaviour. An application to the determination of the gravitational field out of satellite data will be shown.
引用
收藏
页码:303 / 317
页数:15
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