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.
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