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

Wang S.

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

机译：动态矩阵压缩的拟块Cholesky因式分解，用于大规模人体模型的快速积分方程仿真

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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.

机译：本文提出了一种用于模拟人体模型的快速直接积分方程方法。基于阻抗矩阵的混合对称和偏斜对称模式，提出了一种准块Cholesky（QBC）算法，可将用于矩阵分解的内存和中央处理器（CPU）时间减少一半。通过单级自适应交叉逼近（ACA）进行动态矩阵压缩可进一步降低计算成本。提供了QBC方法的有效性。数值算例进一步说明了该方法的实用性。

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来源
《Proceedings of the IEEE》 |2013年第2期|p.389-400|共12页
作者
Wang S.;
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作者单位

Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA;

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正文语种 eng
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关键词
Biological system modeling; Computational efficiency; Heuristic algorithms; Impedance; Manganese; Matrix decomposition; Symmetric matrices; Dielectric bodies; fast direct matrix factorization; method of moments;

机译：生物系统建模;计算效率;启发式算法;阻抗;锰;矩阵分解;对称矩阵电介质体;快速直接矩阵分解;时刻法;

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

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