Optimized wavelet preconditioning

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Title:Main Title: Optimized wavelet preconditioning
Description:Abstract: The numerical solution of linear stationary variational problems involving elliptic partial differential operators usually requires iterative solvers on account of their problem size. Our guiding principle is to devise theoretically and practically efficient iterative solution schemes which are optimal in the number of arithmetic operations, i.e., of linear complexity in the total number of unknowns. For these algorithms, asymptotically optimal preconditioners are indispensable. This article collects the main ingredients for multilevel preconditioners based on wavelets for certain systems of elliptic PDEs with smooth solutions. Specifically, we consider problems from optimal control with distributed or Dirichlet boundary control constrained by elliptic PDEs. Moreover, the wavelet characterization of function space norms will also be used in modelling the control functional, thereby extending the range of applicability over conventional methods. The wavelet preconditioners are optimized for these PDE systems to exhibit small absolute condition numbers and consequently entail absolute low iteration numbers, as numerical experiments show.
Identifier:10.1007/978-3-642-03413-8_10 (DOI)
Responsible Party
Creator:Angela Kunoth (Author)
Publisher:Springer
Publication Year:2013
Topic
TR32 Topic:Other
Related Subprojects:C1, C7
Subject:Keyword: Wavelet
File Details
Filename:2009_Kunoth_Optimized_wavelet_preconditioning.pdf
Data Type:Text - Book Section
Size:54 Pages
File Size:1.6 MB
Date:Issued: 05.09.2009
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
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Download Permission:Only Project Members
General Access and Use Conditions:For internal use only
Access Limitations:For internal use only
Licence:[TR32DB] Data policy agreement
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Specific Information - Publication
Publication Status:Published
Review Status:Peer reviewed
Publication Type:Book Section
Book Title:Multiscale, Nonlinear and Adaptive Approximation
Editors:Ronald DeVore, Angela Kunoth
City:Heidelberg
Number of Pages:54 (325 - 378)
Metadata Details
Metadata Creator:Angela Kunoth
Metadata Created:09.12.2013
Metadata Last Updated:09.12.2013
Subproject:C1
Funding Phase:1
Metadata Language:English
Metadata Version:V50
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