Synopses & Reviews
Multiscale Wavelet Methods for Partial Differential Equations is the sixth volume in the well-respected series Wavelet Analysis and Its Applications. Wavelet methods are well established as a new and powerful mathematical tool with applications in Signal Analysis, Image Processing. Theoretical Physics, and Mathematics. In numerical solution of partial differentail equations, multiscale wavelet methods compete with well-established and effective approach and the standard techniques. It is designed to update current developments in partial differential equations related to the wavelet approach. The fourteen chapters included in this volume were prepared by some of the leading professionals in this developing field, and they delve into the recent advances and future prospects of this methodology specifically in the area of partial differential equations.
Synopsis
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.
Key Features
* 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
Synopsis
Multiscale Wavelet Methods for Partial Differential Equations is the sixth volume in the well-respected series Wavelet Analysis and Its Applications. Wavelet methods are well established as a new and powerful mathematical tool with applications in Signal Analysis, Image Processing. Theoretical Physics, and Mathematics. In numerical solution of partial differentail equations, multiscale wavelet methods compete with well-established and effective approach and the standard techniques. It is designed to update current developments in partial differential equations related to the wavelet approach. The fourteen chapters included in this volume were prepared by some of the leading professionals in this developing field, and they delve into the recent advances and future prospects of this methodology specifically in the area of partial differential equations.
Synopsis
ncluded in this volume were prepared by some of the leading professionals in this developing field, and they delve into the recent advances and future prospects of this methodology specifically in the area of partial differential equations.
Table of Contents
FEM-Like Multilevel Preconditioning: P. Oswald, Multilevel Solvers for Elliptic Problems on Domains.
P. Vassilevski and J. Wang, Wavelet-Like Methods in the Design of Efficient Multilevel Preconditioners for Elliptic PDEs.
Fast Wavelet Algorithms: Compression and Adaptivity: S. Bertoluzza, An Adaptive Collocation Method Based on Interpolating Wavelets.
G. Beylkin and J. Keiser, An Adaptive Pseudo-Wavelet Approach for Solving Nonlinear PartialDifferential Equations.
P. Joly, Y. Maday, and V. Perrier, A Dynamical Adaptive Concept Based on Wavelet Packet Best Bases: Application to Convection Diffusion Partial Differential Equations.
S. Dahlke, W. Dahmen, and R. DeVore, Nonlinear Approximation and Adaptive Techniques for Solving Elliptic Operator Equations.
Wavelet Solvers for Integral Equations: T. von Petersdorff and C. Schwab, Fully Discrete Multiscale Galerkin BEM.
A. Rieder, Wavelet Multilevel Solvers for Linear Ill-Posed Problems Stabilized by Tikhonov Regularization.
Software Tools and Numerical Experiments: T. Barsch, A. Kunoth, and K. Urban, Towards Object Oriented Software Tools for Numerical Multiscale Methods for PDEs Using Wavelets.
J. Ko, A. Kurdila, and P. Oswald, Scaling Function and Wavelet Preconditioners for Second Order Elliptic Problems.
Multiscale Interaction and Applications to Turbulence: J. Elezgaray, G. Berkooz, H. Dankowicz, P. Holmes, and M. Myers, Local Models and Large Scale Statistics of the Kuramoto-Sivashinsky Equation.
M. Wickerhauser, M. Farge, and E. Goirand, Theoretical Dimension and the Complexity of Simulated Turbulence.
Wavelet Analysis of Partial Differential Operators: J-M. Angeletti, S. Mazet, and P. Tchamitchian, Analysis of Second-Order Elliptic Operators Without Boundary Conditions and With VMO or Hilderian Coefficients.
M. Holschneider, Some Directional Elliptic Regularity for Domains with Cusps. Subject Index.