Technical Paper - TH-PM-1 TC9 Numerical Modeling ApproachesUncertainties in realistic lumped and distributive circuit systems are of great importance to today's high yield manufacture demand. However, evaluating the stochastic effect in the time domain for the hybrid electromagnetics (EM)-circuit system was seldom done, especially when Monte Carlo is too expensive to be feasible. In this work, an adaptive hierarchical sparse grid collocation (ASGC) method is presented to quantify the impacts of stochastic inputs on hybrid electromagnetics (EM)-circuit or EM scattering systems. The ASGC method approximates the stochastic observables of interest using interpolation functions over series collocation points. Instead of employing a full-tensor p...
To quantify waveguide dispersion uncertainty, we propose a stochastic analysis technique based on th...
Collocation algorithms for efficiently solving stochastic differential equations arising from modeli...
We discuss computationally efficient ways of accounting for the impact of uncertainty, e. g., lack o...
The stochastic computation of electromagnetic (EM) problems is a relatively new topic, yet very impo...
This thesis presents a set of tools and methodologies that perform fast stochastic characterization ...
This thesis presents methodologies for the efficient assessment of the impact of statistical variabi...
This work proposes a domain adaptive stochastic collocation approach for uncertainty quantification,...
The uncertainties in various Electromagnetic (EM) problems may present a significant effect on the p...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
Variations in material properties, boundary conditions, or the geometry can be expected in most elec...
This paper presents an iterative and decoupled perturbative stochastic Galerkin (SG) method for the ...
Uncertainty analysis methods are widely used in today’s Electromagnetic Compatibility (EMC) simulati...
This dissertation study three different approaches for stochastic electromagnetic fields based on th...
This paper delivers a considerable improvement in the framework of the statistical simulation of hig...
Uncertainties have become a major concern in integrated circuit design. In order to avoid the huge n...
To quantify waveguide dispersion uncertainty, we propose a stochastic analysis technique based on th...
Collocation algorithms for efficiently solving stochastic differential equations arising from modeli...
We discuss computationally efficient ways of accounting for the impact of uncertainty, e. g., lack o...
The stochastic computation of electromagnetic (EM) problems is a relatively new topic, yet very impo...
This thesis presents a set of tools and methodologies that perform fast stochastic characterization ...
This thesis presents methodologies for the efficient assessment of the impact of statistical variabi...
This work proposes a domain adaptive stochastic collocation approach for uncertainty quantification,...
The uncertainties in various Electromagnetic (EM) problems may present a significant effect on the p...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
Variations in material properties, boundary conditions, or the geometry can be expected in most elec...
This paper presents an iterative and decoupled perturbative stochastic Galerkin (SG) method for the ...
Uncertainty analysis methods are widely used in today’s Electromagnetic Compatibility (EMC) simulati...
This dissertation study three different approaches for stochastic electromagnetic fields based on th...
This paper delivers a considerable improvement in the framework of the statistical simulation of hig...
Uncertainties have become a major concern in integrated circuit design. In order to avoid the huge n...
To quantify waveguide dispersion uncertainty, we propose a stochastic analysis technique based on th...
Collocation algorithms for efficiently solving stochastic differential equations arising from modeli...
We discuss computationally efficient ways of accounting for the impact of uncertainty, e. g., lack o...