Indoor environment propagation review
H Obeidat, A Alabdullah, E Elkhazmi, W Suhaib… - Computer Science …, 2020 - Elsevier
A survey of indoor propagation characteristics is presented, including different models for
path loss, shadowing and fast fading mechanisms, different channel parameters including …
path loss, shadowing and fast fading mechanisms, different channel parameters including …
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 …
Efficient analysis of geometrical uncertainty in the FDTD method using polynomial chaos with application to microwave circuits
ACM Austin, CD Sarris - IEEE Transactions on Microwave …, 2013 - ieeexplore.ieee.org
A novel finite-difference time-domain (FDTD)-based method is developed to analyze 3-D
microwave circuits with uncertain parameters, such as variability and tolerances in the …
microwave circuits with uncertain parameters, such as variability and tolerances in the …
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 …
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 …
Rapid design centering of multi-band antennas using knowledge-based inverse models and response features
S Koziel, A Pietrenko-Dabrowska - Knowledge-Based Systems, 2022 - Elsevier
Accounting for manufacturing tolerances as well as uncertainties concerning operating
conditions and material parameters is one of the important yet often neglected aspects of …
conditions and material parameters is one of the important yet often neglected aspects of …
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 …
Integrating physics-based wireless propagation models and network protocol design for train communication systems
Physics-based wireless propagation modeling and network protocol design have evolved
over decades as orthogonal areas in communication systems research. This fragmented …
over decades as orthogonal areas in communication systems research. This fragmented …
Uncertainty quantification in transcranial magnetic stimulation via high-dimensional model representation
A computational framework for uncertainty quantification in transcranial magnetic stimulation
(TMS) is presented. The framework leverages high-dimensional model representations …
(TMS) is presented. The framework leverages high-dimensional model representations …
A novel surrogate-based approach to yield estimation and optimization of microwave structures using combined quadratic mappings and matrix transfer functions
Yield estimation and yield-driven design optimization play important roles in microwave
design. Existing surrogate-based yield estimation/optimization methods need to develop …
design. Existing surrogate-based yield estimation/optimization methods need to develop …