Finite-difference time-domain methods
The finite-difference time-domain (FDTD) method is a widespread numerical tool for full-
wave analysis of electromagnetic fields in complex media and for detailed geometries …
wave analysis of electromagnetic fields in complex media and for detailed geometries …
Polynomial chaos-based approach to yield-driven EM optimization
Yield-driven optimization is important in microwave design due to the uncertainties
introduced in the manufacturing process. For the first time, we extend in this paper the use of …
introduced in the manufacturing process. For the first time, we extend in this paper the use of …
An ME-PC enhanced HDMR method for efficient statistical analysis of multiconductor transmission line networks
An efficient method for statistically characterizing multiconductor transmission line (MTL)
networks subject to a large number of manufacturing uncertainties is presented. The …
networks subject to a large number of manufacturing uncertainties is presented. The …
An efficient technique based on polynomial chaos to model the uncertainty in the resonance frequency of textile antennas due to bending
F Boeykens, H Rogier, L Vallozzi - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
The generalized polynomial chaos theory is combined with a dedicated cavity model for
curved textile antennas to statistically quantify variations in the antenna's resonance …
curved textile antennas to statistically quantify variations in the antenna's resonance …
A stochastic framework for the variability analysis of textile antennas
A novel framework to accurately quantify the effect of stochastic variations of design
parameters on the performance of textile antennas is developed and tested. First, a …
parameters on the performance of textile antennas is developed and tested. First, a …
Probabilistic uncertainty quantification of microwave circuits using Gaussian processes
P Manfredi - IEEE Transactions on Microwave Theory and …, 2022 - ieeexplore.ieee.org
In this article, a probabilistic machine learning framework based on Gaussian process
regression (GPR) and principal component analysis (PCA) is proposed for the uncertainty …
regression (GPR) and principal component analysis (PCA) is proposed for the uncertainty …
A 3-D stochastic FDTD model of electromagnetic wave propagation in magnetized ionosphere plasma
A stochastic finite-difference time-domain (S-FDTD) algorithm is presented for
electromagnetic-wave propagation in anisotropic magnetized plasma. This new algorithm …
electromagnetic-wave propagation in anisotropic magnetized plasma. This new algorithm …
Adaptively weighted yield-driven EM optimization incorporating neurotransfer function surrogate with applications to microwave filters
In this article, we propose an adaptively weighted yield-driven EM optimization technique
incorporating neurotransfer function (neuro-TF) surrogate. In the proposed technique, an …
incorporating neurotransfer function (neuro-TF) surrogate. In the proposed technique, an …
Efficient statistical simulation of microwave devices via stochastic testing-based circuit equivalents of nonlinear components
P Manfredi, FG Canavero - IEEE Transactions on Microwave …, 2015 - ieeexplore.ieee.org
This paper delivers a considerable improvement in the framework of the statistical simulation
of highly nonlinear devices via polynomial chaos-based circuit equivalents. Specifically, a …
of highly nonlinear devices via polynomial chaos-based circuit equivalents. Specifically, a …
Parallel space-mapping based yield-driven EM optimization incorporating trust region algorithm and polynomial chaos expansion
Space mapping (SM) methodology has been recognized as a powerful tool for accelerating
electromagnetic (EM)-based yield optimization. This paper proposes a novel parallel space …
electromagnetic (EM)-based yield optimization. This paper proposes a novel parallel space …