2019
DOI: 10.1109/tmtt.2019.2948873
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Sparsity-Aware Precorrected Tensor Train Algorithm for Fast Solution of 2-D Scattering Problems and Current Flow Modeling on Unstructured Meshes

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Cited by 9 publications
(2 citation statements)
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“…So far, a plethora of methods has been developed to lower the memory and CPU time requirements of VIE solvers [4]- [12]. These methods were primarily developed to expedite the matrix-vector multiplications during the iterative solution of the VIE system.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…So far, a plethora of methods has been developed to lower the memory and CPU time requirements of VIE solvers [4]- [12]. These methods were primarily developed to expedite the matrix-vector multiplications during the iterative solution of the VIE system.…”
Section: Introductionmentioning
confidence: 99%
“…These methods were primarily developed to expedite the matrix-vector multiplications during the iterative solution of the VIE system. They leverage analytic or algebraic compression techniques, including the fast multipole method (FMM) [4], [5], fast Fourier transform [6]- [8], [13], low-rank compression [9], hierarchical matrices as kernel-free FMM [10], [11], and, more recently, tensor decompositions [12]. Despite the success of these methods in expediting matrixvector multiplications during iterative solution, the discretized VIE systems are often ill-conditioned.…”
Section: Introductionmentioning
confidence: 99%