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  1. Foundations of Computational Mathematics
  2. Foundations of Computational Mathematics : Volume 14
  3. Foundations of Computational Mathematics : Volume 14, Issue 2, April 2014
  4. Parabolic Molecules
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Foundations of Computational Mathematics : Volume 17
Foundations of Computational Mathematics : Volume 16
Foundations of Computational Mathematics : Volume 15
Foundations of Computational Mathematics : Volume 14
Foundations of Computational Mathematics : Volume 14, Issue 6, December 2014
Foundations of Computational Mathematics : Volume 14, Issue 5, October 2014
Foundations of Computational Mathematics : Volume 14, Issue 4, August 2014
Foundations of Computational Mathematics : Volume 14, Issue 3, June 2014
Foundations of Computational Mathematics : Volume 14, Issue 2, April 2014
Complexity of Path-Following Methods for the Eigenvalue Problem
Adaptive Wavelet Methods for Linear and Nonlinear Least-Squares Problems
On the Distribution of Atkin and Elkies Primes
Parabolic Molecules
Geometric Generalisations of shake and rattle
Efficient Recognition of Totally Nonnegative Matrix Cells
Foundations of Computational Mathematics : Volume 14, Issue 1, February 2014
Foundations of Computational Mathematics : Volume 13
Foundations of Computational Mathematics : Volume 12
Foundations of Computational Mathematics : Volume 11
Foundations of Computational Mathematics : Volume 10
Foundations of Computational Mathematics : Volume 9
Foundations of Computational Mathematics : Volume 8
Foundations of Computational Mathematics : Volume 7
Foundations of Computational Mathematics : Volume 6
Foundations of Computational Mathematics : Volume 5
Foundations of Computational Mathematics : Volume 4
Foundations of Computational Mathematics : Volume 3
Foundations of Computational Mathematics : Volume 2
Foundations of Computational Mathematics : Volume 1

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Parabolic Molecules

Content Provider Springer Nature Link
Author Kutyniok, Gitta Grohs, Philipp
Copyright Year 2013
Abstract Anisotropic decompositions using representation systems based on parabolic scaling such as curvelets or shearlets have recently attracted significant attention due to the fact that they were shown to provide optimally sparse approximations of functions exhibiting singularities on lower dimensional embedded manifolds. The literature now contains various direct proofs of this fact and of related sparse approximation results. However, it seems quite cumbersome to prove such a canon of results for each system separately, while many of the systems exhibit certain similarities.In this paper, with the introduction of the notion of parabolic molecules, we aim to provide a comprehensive framework which includes customarily employed representation systems based on parabolic scaling such as curvelets and shearlets. It is shown that pairs of parabolic molecules have the fundamental property to be almost orthogonal in a particular sense. This result is then applied to analyze parabolic molecules with respect to their ability to sparsely approximate data governed by anisotropic features. For this, the concept of sparsity equivalence is introduced which is shown to allow the identification of a large class of parabolic molecules providing the same sparse approximation results as curvelets and shearlets. Finally, as another application, smoothness spaces associated with parabolic molecules are introduced providing a general theoretical approach which even leads to novel results for, for instance, compactly supported shearlets.
Ending Page 337
Page Count 39
Starting Page 299
File Format PDF
ISSN 16153375
e-ISSN 16153383
Journal Foundations of Computational Mathematics
Issue Number 2
Volume Number 14
Language English
Publisher Springer US
Publisher Date 2013-09-17
Publisher Place Boston
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Economics general Parabolic scaling Shearlets Linear and Multilinear Algebras, Matrix Theory Smoothness spaces Curvelets Sparsity equivalence Numerical Analysis Computer Science Applications of Mathematics Math Applications in Computer Science Nonlinear approximation Rate of convergence, degree of approximation
Content Type Text
Resource Type Article
Subject Applied Mathematics Analysis Computational Theory and Mathematics Computational Mathematics
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