A wavelet-based approach for compressing kernel data in large-scale simulations of 3D integral problems

Authors:
Kevin Amaratunga
Affiliations:
-
Venue:
Computing in Science and Engineering
Year:
2000

Citing 8
Cited 2

A fast algorithm for particle simulations

Journal of Computational Physics
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Ten lectures on wavelets

Ten lectures on wavelets
Preconditioned, adaptive, multipole-accelerated iterative methods for three-dimensional first-kind integral equations of potential theory

SIAM Journal on Scientific Computing
Multipole translation theory for the three-dimensional Laplace and Helmholtz equations

SIAM Journal on Scientific Computing
Spherical wavelets: efficiently representing functions on the sphere

SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Interpolating Subdivision for meshes with arbitrary topology

SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Iterative methods for large, sparse, nonsymmetric systems of linear equations

Iterative methods for large, sparse, nonsymmetric systems of linear equations

Open source BEM library

Advances in Engineering Software
A new algorithm for generalized wavelet transform

ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

Second-generation surface wavelets can be an effective tool for compressing integral operator matrices arising from large-scale simulations of 3D problems. The author's approach generalizes previously reported results on wavelet-based operator compression to nonuniform grids and fairly general domains.