Introduction to Hierarchical Matrices with Applications
By Steffen Börm, Lars Grasedyck, Wolfgang Hackbusch. 2003
513 citations recorded by the source corpus.
Subfields: Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering, Mechanics of Materials
View Paper: https://www.semanticscholar.org/paper/5b4f3a38272d8c62be72dd06de99d836783aa48d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Atomic and Molecular Physics, and Optics
- Lars Grasedyck
- Wolfgang Hackbusch
- Jianlin Xia
- Maarten V. de Hoop
- Shen Wang
- Carsten H. Wolters
- Boris N. Khoromskij
- Steffen Börm
In Electrical and Electronic Engineering
- Jianlin Xia
- Lars Grasedyck
- Maarten V. de Hoop
- Shen Wang
- Wolfgang Hackbusch
- Carsten H. Wolters
- David J. Biagioni
In Mechanics of Materials
Citations in the corpus
- On 3D modeling of seismic wave propagation via a structured parallel multifrontal direct Helmholtz solver (2011, methodology): “We can approximate a dense matrix F whose off-diagonal blocks have small numerical ranks by rank-structured matrices such as H-matrices (Hackbusch 1999; Hackbusch and Börm 2002; Hackbusch and Khoromskij 2000), H2-matrices (Börm et al. 2003; Börm and Hackbusch; Hackbusch and Sauter 2000), semisepa”
- Existence and Computation of Low Kronecker-Rank Approximations for Large Linear Systems of Tensor Product Structure (2004, methodology): “More details concerning the H-matrix arithmetic and the treatment of higher dimensional problems can be found in [5] and an introduction with applications is given in [ 2 ].”
- Efficient Computation of Lead Field Bases and Influence Matrix for the FEM-based EEG and MEG Inverse Problem. Part I: Complexity Considerations (2003, methodology): “A new technique to store matrices of this type in a data-sparse form are so-called hierarchical matrices, or short H-matrices [47–50].”