2,451 research outputs found
Optimal Approximation of Elliptic Problems by Linear and Nonlinear Mappings III: Frames
We study the optimal approximation of the solution of an operator equation by
certain n-term approximations with respect to specific classes of frames. We
study worst case errors and the optimal order of convergence and define
suitable nonlinear frame widths.
The main advantage of frames compared to Riesz basis, which were studied in
our earlier papers, is the fact that we can now handle arbitrary bounded
Lipschitz domains--also for the upper bounds.
Key words: elliptic operator equation, worst case error, frames, nonlinear
approximation, best n-term approximation, manifold width, Besov spaces on
Lipschitz domainsComment: J. Complexity, to appear. Final version, minor mistakes correcte
Shearlets and Optimally Sparse Approximations
Multivariate functions are typically governed by anisotropic features such as
edges in images or shock fronts in solutions of transport-dominated equations.
One major goal both for the purpose of compression as well as for an efficient
analysis is the provision of optimally sparse approximations of such functions.
Recently, cartoon-like images were introduced in 2D and 3D as a suitable model
class, and approximation properties were measured by considering the decay rate
of the error of the best -term approximation. Shearlet systems are to
date the only representation system, which provide optimally sparse
approximations of this model class in 2D as well as 3D. Even more, in contrast
to all other directional representation systems, a theory for compactly
supported shearlet frames was derived which moreover also satisfy this
optimality benchmark. This chapter shall serve as an introduction to and a
survey about sparse approximations of cartoon-like images by band-limited and
also compactly supported shearlet frames as well as a reference for the
state-of-the-art of this research field.Comment: in "Shearlets: Multiscale Analysis for Multivariate Data",
Birkh\"auser-Springe
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