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Degree:Doctoral Degree in Philosophy
School/Department:College of Electronic and Information Engineering

曹群生

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Gender:Male

Education Level:With Certificate of Graduation for Doctorate Study

Paper Publications

Multiscale Compressed and Spliced Sherman-Morrison-Woodbury Algorithm With Characteristic Basis Function Method
Date of Publication:2018-06-01 Hits:

Affiliation of Author(s):电子信息工程学院
Journal:IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY
Key Words:Adaptive cross approximation (ACA) characteristic basis function method (CBFM) fast direct solver method of moments (MoM) multiscale compression and splicing (MSCS) Sherman-Morrison-Woodbury (SMW) formula
Abstract:In this paper, a multiscale compressed and spliced Sherman-Morrison-Woodbury algorithm (MSCS-SMWA), based on the characteristic basis function method (CBFM), has been presented to accelerate direct solutions of electromagnetic scattering. The impedance matrix or reduced matrix can be compressed into block diagonal matrices with the adaptive cross approximation (ACA) and easily obtained the matrix inverse with this method. The MSCS-SMWA method is combined with a multiscale compressed ACA and a multiscale spliced singular value decomposition (SVD). The numerical results of several perfect electric conducting (PEC) objects are validated to demonstrate the performance of this method. Compared with the conventional methods, SMWA with the ACA and CBFM, the simulation results of the proposal method have been shown that the computation time and storage requirements have reduced about 10.77% and 44.22%, for the sphere with 10 lambda radius. Also, it costs 49.16% less CPU time and 1.54% less memory than the conventional method with SVD.
ISSN No.:0018-9375
Translation or Not:no
Date of Publication:2018-06-01
Co-author:Fang, Xiaoxing,Wang Yi
Correspondence Author:cqs
Date of Publication:2018-06-01