Quasi-Block-Cholesky Factorization With Dynamic Matrix Compression for Fast Integral-Equation Simulations of Large-Scale Human Body Models

Author

Shumin Wang

Author_Institution

Dept. of Electr. & Comput. Eng., Auburn Univ., Auburn, AL, USA

Volume

101

Issue

2

fYear

2013

Firstpage

389

Lastpage

400

Abstract

In this paper, a fast direct integral-equation method for simulating human models is presented. Based on the mixed symmetric and skew-symmetric pattern of the impedance matrix, a quasi-block-Cholesky (QBC) algorithm was proposed to reduce both the memory and central processing unit (CPU) time for matrix factorization by half. Dynamic matrix compression via single-level adaptive cross approximation (ACA) was further applied to reduce the computational costs. Validity of the QBC method is provided. Numerical examples further demonstrate the practicality of the proposed method.

Keywords

integral equations; matrix decomposition; medical computing; ACA; CPU; QBC algorithm; central processing unit; direct integral-equation method; dynamic matrix compression; impedance matrix; large-scale human body model; matrix factorization; quasiblock-Cholesky factorization; single-level adaptive cross approximation; skew-symmetric pattern; Biological system modeling; Computational efficiency; Dielectric materials; Heuristic algorithms; Impedance; Matrix decomposition; Moment methods; Symmetric matrices; Dielectric bodies; fast direct matrix factorization; method of moments;

fLanguage

English

Journal_Title

Proceedings of the IEEE

Publisher

ieee

ISSN

0018-9219

Type

jour

DOI

10.1109/JPROC.2012.2192889

Filename

6210347