Compressed representation of matrix decomposition algorithm-singular value decomposition for full-wave analysis microstrip problems

Abstract

In order to efficiently solve large dense complex linear systems arising from electric field integral equations (EFIE) of electromagnetic problems, matrix decomposition algorithm-singular value decomposition (MDA-SVD) is used to accelerate the matrix-vector product (MVP) operations and decrease memory usage. Based on the symmetry of the impedance matrix resulting from the discretization of the EFIE, we introduce a compressed representation of MDA-SVD in this paper. We obtain a sparse representation of the far-field interaction parts of impedance matrix and perform a fast MVP operation. Numerical experiments demonstrate that the compressed representation of MDA-SVD can reduce both the MVP time and memory usage by around 50% with similar accuracy.

Keywords:

• electromagnetic theory
• microstrip
• method of moment (MoM)
• matrix decomposition algorithm-singular value decomposition (MDA-SVD)
• electromagnetic radiation

Acknowledgments

The authors would like to thank Prof. Y.C. Chung for his useful suggestions and discussions.

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China [grant number 51307171], [grant number 61401450]; major scientific instrument research of National Natural Science Foundation of China [grant number 81327801]; SIAT Innovation Program for Excellent Young Researchers [grant number 201314].