Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Cam Key"'
Publikováno v:
IEEE Transactions on Antennas and Propagation. 69:6669-6679
We present an application of adjoint analysis for efficient sensitivity analysis and estimation of quantities of interest in the presence of uncertain model parameters in 3-D finite element method (FEM) scattering problems. We demonstrate that the ad
Publikováno v:
IEEE Transactions on Antennas and Propagation. 69:4808-4815
We propose and evaluate several improvements to the accuracy of the shooting and bouncing ray (SBR) method for ray-tracing (RT) electromagnetic modeling. We propose per-ray cone angle calculation, with the maximum separation angle between rays calcul
Autor:
Cam Key, Branislav M. Notaros
Publikováno v:
IEEE Antennas and Wireless Propagation Letters. 20:1200-1204
In this letter, we present research on the application of deep neural networks to predicting macro basis functions for complicated computational electromagnetics problems. We provide error statistics and representative examples for networks trained o
Publikováno v:
IEEE Antennas and Wireless Propagation Letters. 20:2516-2518
Publikováno v:
IEEE Transactions on Antennas and Propagation. 69:940-949
We present the application of adjoint analysis to 3-D finite-element method scattering problems for a posteriori error estimation and adaptive refinement. Adjoint-based methodologies, though underutilized in computational electromagnetics (CEM), enab
Publikováno v:
IEEE Transactions on Antennas and Propagation. 69:332-346
We propose a surface meshing approach for computational electromagnetics (CEM) based on discrete surface Ricci flow (DSRF) with iterative adaptive refinement (AR) in the parametric domain for the automated generation of high-quality surface meshes of
Publikováno v:
IEEE Transactions on Antennas and Propagation. 68:3791-3806
This study investigates and evaluates applications of the adjoint problem and its solution in frequency-domain computational electromagnetics (CEM). The study establishes and validates adjoint-based applications including higher order parameter sampl
Autor:
Branislav M. Notaros, Cam Key
Publikováno v:
IEEE Antennas and Wireless Propagation Letters. 19:626-630
In this letter, we propose and demonstrate a data-driven machine learning-based approach to accelerate the finite element method (FEM), method of moments (MoM), finite difference (FD) method, and related variational methods, while maintaining the att
Publikováno v:
IEEE Journal on Multiscale and Multiphysics Computational Techniques. 5:245-254
We propose and experimentally validate a new ray spawning and associated double count removal (DCR) technique for shooting–bouncing ray tracing (SBR). This technique allows, for the first time, efficient parallelization of ray DCR, the major bottle
Publikováno v:
Journal of Atmospheric and Oceanic Technology.
We present improvements over our previous approach to automatic winter hydrometeor classification by means of convolutional neural networks (CNNs), using more data and improved training techniques to achieve higher accuracy on a more complicated data