A Cholesky-Based SGM-MLFMM for Stochastic Full-Wave Problems Described by Correlated Random Variables
In this letter, the multilevel fast multipole method (MLFMM) is combined with the polynomial chaos expansion (PCE)-based stochastic Galerkin method (SGM) to stochastically model scatterers with geometrical variations that need to be described by a set of correlated random variables (RVs). It is demo...
Main Authors: | Zubac, Zdravko, De Zutter, Daniel, Vande Ginste, Dries, Daniel, Luca |
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Other Authors: | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
Format: | Article |
Language: | en_US |
Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2017
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Online Access: | http://hdl.handle.net/1721.1/110827 https://orcid.org/0000-0002-5880-3151 |
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