Fast Solution of High Stochastic Dimensional EM Problems Using Proper Orthogonal Decomposition
Author:
Affiliation:
1. Department of Electrical Communication Engineering, Indian Institute of Science, Bengaluru, India
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Condensed Matter Physics
Link
http://xplorestaging.ieee.org/ielx7/7260/9789504/09712616.pdf?arnumber=9712616
Reference24 articles.
1. Neumann-Expansion-Based FEM for Uncertainty Quantification of Permittivity Variations
2. A POD-based reduced-order model for free surface shallow water flows over real bathymetries for Monte-Carlo-type applications
3. Non-linear model reduction for uncertainty quantification in large-scale inverse problems;galbally;Int J Numer Meth Engng,2010
4. Reduction of a Finite-Element Parametric Model Using Adaptive POD Methods—Application to Uncertainty Quantification
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1. A Nonintrusive POD-PCE Scheme for Uncertainty Quantification of Stochastic EM Problems;IEEE Microwave and Wireless Technology Letters;2023-08
2. An Efficient SSFEM-POD Scheme for Wideband Stochastic Analysis of Permittivity Variations;IEEE Transactions on Antennas and Propagation;2023-02
3. Probabilistic Uncertainty Quantification of Microwave Circuits Using Gaussian Processes;IEEE Transactions on Microwave Theory and Techniques;2022
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