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Wavelet Methods for Elliptic Partial Differential Equations

Wavelet Methods for Elliptic Partial Differential Equations
Author: Karsten Urban
Publisher: OUP Oxford
Total Pages: 512
Release: 2008-11-27
Genre: Mathematics
ISBN: 0191523526

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The origins of wavelets go back to the beginning of the last century and wavelet methods are by now a well-known tool in image processing (jpeg2000). These functions have, however, been used successfully in other areas, such as elliptic partial differential equations, which can be used to model many processes in science and engineering. This book, based on the author's course and accessible to those with basic knowledge of analysis and numerical mathematics, gives an introduction to wavelet methods in general and then describes their application for the numerical solution of elliptic partial differential equations. Recently developed adaptive methods are also covered and each scheme is complemented with numerical results, exercises, and corresponding software tools.


Adaptive Wavelet Methods for Variational Formulations of Nonlinear Elliptic PDEs on Tensor-Product Domains

Adaptive Wavelet Methods for Variational Formulations of Nonlinear Elliptic PDEs on Tensor-Product Domains
Author: Roland Pabel
Publisher: Logos Verlag Berlin GmbH
Total Pages: 336
Release: 2015-09-30
Genre: Mathematics
ISBN: 3832541020

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This thesis is concerned with the numerical solution of boundary value problems (BVPs) governed by nonlinear elliptic partial differential equations (PDEs). To iteratively solve such BVPs, it is of primal importance to develop efficient schemes that guarantee convergence of the numerically approximated PDE solutions towards the exact solution. The new adaptive wavelet theory guarantees convergence of adaptive schemes with fixed approximation rates. Furthermore, optimal, i.e., linear, complexity estimates of such adaptive solution methods have been established. These achievements are possible since wavelets allow for a completely new perspective to attack BVPs: namely, to represent PDEs in their original infinite dimensional realm. Wavelets in this context represent function bases with special analytical properties, e.g., the wavelets considered herein are piecewise polynomials, have compact support and norm equivalences between certain function spaces and the $ell_2$ sequence spaces of expansion coefficients exist. This theoretical framework is implemented in the course of this thesis in a truly dimensionally unrestricted adaptive wavelet program code, which allows one to harness the proven theoretical results for the first time when numerically solving the above mentioned BVPs. Numerical studies of 2D and 3D PDEs and BVPs demonstrate the feasibility and performance of the developed schemes. The BVPs are solved using an adaptive Uzawa algorithm, which requires repeated solution of nonlinear PDE sub-problems. This thesis presents for the first time a numerically competitive implementation of a new theoretical paradigm to solve nonlinear elliptic PDEs in arbitrary space dimensions with a complete convergence and complexity theory.


Numerical Analysis of Wavelet Methods

Numerical Analysis of Wavelet Methods
Author: A. Cohen
Publisher: Elsevier
Total Pages: 357
Release: 2003-04-29
Genre: Mathematics
ISBN: 0080537855

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Since their introduction in the 1980's, wavelets have become a powerful tool in mathematical analysis, with applications such as image compression, statistical estimation and numerical simulation of partial differential equations. One of their main attractive features is the ability to accurately represent fairly general functions with a small number of adaptively chosen wavelet coefficients, as well as to characterize the smoothness of such functions from the numerical behaviour of these coefficients. The theoretical pillar that underlies such properties involves approximation theory and function spaces, and plays a pivotal role in the analysis of wavelet-based numerical methods. This book offers a self-contained treatment of wavelets, which includes this theoretical pillar and it applications to the numerical treatment of partial differential equations. Its key features are: 1. Self-contained introduction to wavelet bases and related numerical algorithms, from the simplest examples to the most numerically useful general constructions. 2. Full treatment of the theoretical foundations that are crucial for the analysis of wavelets and other related multiscale methods : function spaces, linear and nonlinear approximation, interpolation theory. 3. Applications of these concepts to the numerical treatment of partial differential equations : multilevel preconditioning, sparse approximations of differential and integral operators, adaptive discretization strategies.


Adaptive Wavelet and Frame Schemes for Elliptic and Parabolic Equations

Adaptive Wavelet and Frame Schemes for Elliptic and Parabolic Equations
Author: Thorsten Raasch
Publisher:
Total Pages: 0
Release: 2007
Genre:
ISBN: 9783832515829

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This thesis is concerned with the application of wavelet methods to the adaptive numerical solutionof elliptic and parabolic operator equations over a polygonal domain. Driven by the insight that the construction of wavelet bases on more general domains is complicated and may pose stability problems, we analyze the option to replace the concept of wavelet bases by the more flexible concept of wavelet frames. Frames are redundant systems that still allow for stable decomposition and reconstruction of a given function. In the first part of this thesis, is shown how to construct so-called Gelfand frames on polygonal domains by a simple overlapping domain decomposition approach. Gelfand frames are able to characterize function spaces in a similar way as in the case of wavelet bases. The second part is concerned with the application of Gelfand frames to the adaptive numerical treatment of linear elliptic problems. We propose inexact versions of well-known iterative schemes for the frame coordinate representation of the given operator equation. Both convergence and optimality of the considered methods can be proved and illustrated by numerical examples. In the third part, we consider adaptive wavelet methods for the numerical treatment of linear parabolic equations. Due to the initial value problem structure, we consider a semidiscretization in time with linearly implicit methods first. The arising sequence of elliptic operator equations is then solved adaptively with wavelet methods. It is shown how to exploit the key properties of wavelet bases to a considerable extent, e.g., in preconditioning strategies and for the convergence and complexity analysis of the overall algorithm. We finish with numerical experiments in one and two spatial dimensions.


Adaptive Wavelet Schwarz Methods for Nonlinear Elliptic Partial Differential Equations

Adaptive Wavelet Schwarz Methods for Nonlinear Elliptic Partial Differential Equations
Author: Dominik Lellek
Publisher:
Total Pages: 0
Release: 2015
Genre: Decomposition (Mathematics)
ISBN: 9783832540678

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Adaptive wavelet methods have recently proven to be a very powerful instrument for the numerical treatment of nonlinear partial differential equations. In many cases, these methods can be shown to converge with an optimal rate with respect to the degrees of freedom and in linear complexity. In this thesis, we couple such algorithms with nonlinear Schwarz domain decomposition techniques. With this approach, we can develop efficient parallel adaptive wavelet Schwarz methods for a class of nonlinear problems and prove their convergence and optimality. We support the theoretical findings with instructive numerical experiments. In addition, we present how these techniques can be applied to the stationary, incompressible Navier-Stokes equation. Furthermore, we couple the adaptive wavelet Schwarz methods with a Newton-type method.


Wavelet Methods — Elliptic Boundary Value Problems and Control Problems

Wavelet Methods — Elliptic Boundary Value Problems and Control Problems
Author: Angela Kunoth
Publisher: Springer Science & Business Media
Total Pages: 150
Release: 2012-12-06
Genre: Mathematics
ISBN: 332280027X

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Diese Monographie spannt einen Bogen rund um die aktuelle Thematik Wavelets, um neueste Entwicklungen anhand aufeinander aufbauender Probleme darzustellen und das konzeptuelle Potenzial von Waveletmethoden für Partielle Differentialgleichungen zu demonstrieren.


Multiscale Wavelet Methods for Partial Differential Equations

Multiscale Wavelet Methods for Partial Differential Equations
Author: Wolfgang Dahmen
Publisher: Elsevier
Total Pages: 587
Release: 1997-08-13
Genre: Mathematics
ISBN: 0080537146

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This latest volume in the Wavelets Analysis and Its Applications Series provides significant and up-to-date insights into recent developments in the field of wavelet constructions in connection with partial differential equations. Specialists in numerical applications and engineers in a variety of fields will find Multiscale Wavelet for Partial Differential Equations to be a valuable resource. Covers important areas of computational mechanics such as elasticity and computational fluid dynamics Includes a clear study of turbulence modeling Contains recent research on multiresolution analyses with operator-adapted wavelet discretizations Presents well-documented numerical experiments connected with the development of algorithms, useful in specific applications


Sparse Grids and Applications - Munich 2012

Sparse Grids and Applications - Munich 2012
Author: Jochen Garcke
Publisher: Springer Science & Business Media
Total Pages: 345
Release: 2014-04-11
Genre: Mathematics
ISBN: 3319045377

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Sparse grids have gained increasing interest in recent years for the numerical treatment of high-dimensional problems. Whereas classical numerical discretization schemes fail in more than three or four dimensions, sparse grids make it possible to overcome the “curse” of dimensionality to some degree, extending the number of dimensions that can be dealt with. This volume of LNCSE collects the papers from the proceedings of the second workshop on sparse grids and applications, demonstrating once again the importance of this numerical discretization scheme. The selected articles present recent advances on the numerical analysis of sparse grids as well as efficient data structures, and the range of applications extends to uncertainty quantification settings and clustering, to name but a few examples.