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Learning-Based Fast Iterative Convergence of 3-D MoM via Eigen-AGMRES Method

Chatterjee, Gourav and Das, Arkaprovo and Gope, Dipanjan (2015) Learning-Based Fast Iterative Convergence of 3-D MoM via Eigen-AGMRES Method. In: IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, 63 (12). pp. 5889-5893.

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Official URL: http://dx.doi.org/10.1109/TAP.2015.2481478


Three-dimensional (3-D) full-wave electromagnetic simulation using method of moments (MoM) under the framework of fast solver algorithms like fast multipole method (FMM) is often bottlenecked by the speed of convergence of the Krylov-subspace-based iterative process. This is primarily because the electric field integral equation (EFIE) matrix, even with cutting-edge preconditioning techniques, often exhibits bad spectral properties arising from frequency or geometry-based ill-conditioning, which render iterative solvers slow to converge or stagnate occasionally. In this communication, a novel technique to expedite the convergence of MoMmatrix solution at a specific frequency is proposed, by extracting and applying Eigen-vectors from a previously solved neighboring frequency in an augmented generalized minimum residual (AGMRES) iterative framework. This technique can be applied in unison with any preconditioner. Numerical results demonstrate up to 40% speed-up in convergence using the proposed Eigen-AGMRES method.

Item Type: Journal Article
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Additional Information: Copy right for this article belongs to the IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Keywords: Augmented generalized minimum residual (AGMRES); electric field integral equation (EFIE); iterative solver
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 10 Feb 2016 05:52
Last Modified: 10 Feb 2016 05:52
URI: http://eprints.iisc.ernet.in/id/eprint/53208

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