Titlebook: Extraction of Quantifiable Information from Complex Systems; Stephan Dahlke,Wolfgang Dahmen,Harry Yserentant Book 2014 Springer Internatio

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Book 2014ion from Complex Systems.” This volume presents a comprehensive overview of the most important results obtained over the course of the program. Mathematical models of complex systems provide the foundation for further technological developments in science, engineering and computational finance. Moti

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https://doi.org/10.1007/978-3-319-43760-6ementation. For the upper confidence bounds we suggest a multilevel simulation within a nested Monte Carlo approach and, alternatively, a generic sieve optimization approach with a variance penalty term.

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https://doi.org/10.1007/978-3-322-93756-8h recovery error estimates when adequately relating the isometry constant of the sensing operator, the ill-posedness of the underlying model operator and the regularization parameter. Finally, we very briefly sketch how projected steepest descent iterations can be applied to retrieve the sparse solution.

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Regularity of the Parameter-to-State Map of a Parabolic Partial Differential Equation,r equations on nontrivial domains as well as with related inverse parameter identification problems. In this paper we study analytic properties of the underlying parameter-to-state map, which is motivated by a parabolic model for the embryonal development of drosophila melanogaster.

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