Results 91 to 100 of about 1,606 (214)

Influence of Head Tissue Conductivity Uncertainties on EEG Dipole Reconstruction

Frontiers in Neuroscience, 2019
Reliable EEG source analysis depends on sufficiently detailed and accurate head models. In this study, we investigate how uncertainties inherent to the experimentally determined conductivity values of the different conductive compartments influence the ...
Johannes Vorwerk, Johannes Vorwerk, Johannes Vorwerk, Ümit Aydin, Ümit Aydin, Carsten H. Wolters, Carsten H. Wolters, Christopher R. Butson, Christopher R. Butson, Christopher R. Butson   +9 more
doaj   +1 more source

Deforming the Double‐Scaled SYK and Reaching the Stretched Horizon From Finite Cutoff Holography

Fortschritte der Physik, Volume 74, Issue 5, May 2026.
ABSTRACT We study the properties of the double‐scaled SYK (DSSYK) model under chord Hamiltonian deformations based on finite cutoff holography for general dilaton gravity theories with Dirichlet boundaries. The formalism immediately incorporates a lower‐dimensional analog of TT¯(+Λ2)$\text{T}\overline{\text{T}}(+\Lambda _2)$ deformations, denoted T2 ...
Sergio E. Aguilar‐Gutierrez
wiley   +1 more source

Time-Dependent Polynomial Chaos

, 2006
Generalized polynomial chaos is known to fail for long-term integration, loosing its optimal convergence behavior and developing unacceptable error-levels.
Vos, P. (author)
core  

Robust Trajectory Optimization of a Ski Jumper for Uncertainty Influence and Safety Quantification

Proceedings, 2018
This paper deals with the development of a robust optimal control framework for a previously developed multi-body ski jumper simulation model by the authors.
Patrick Piprek, Florian Holzapfel
doaj   +1 more source

Generative modeling with low-rank Wasserstein polynomial chaos expansions

, 2022
A new Wasserstein multi-element polynomial chaos expansion (WPCE) is proposed, which is inspired by recent advances in computational optimal transport for estimating Wasserstein distances. The developed method combines unsupervised learning with the explicit functional representation of a random vector $Y$.
Gruhlke, Robert, Eigel, Martin
openaire   +2 more sources

Existence of chaos and the approximate solution of the Lorenz–Lü–Chen system with the Caputo fractional operator

AIP Advances
Dynamical systems and fractional differential equations can be modeled using variable-order differential operators. In this study, the dynamics of a variable-order fractional Lorenz–Lü–Chen system with variable-order and constant-order derivatives are ...
Najat Almutairi, Sayed Saber
doaj   +1 more source

Uncertainty-Aware Computational Tools for Power Distribution Networks Including Electrical Vehicle Charging and Load Profiles

IEEE Access, 2019
As new services and business models are being associated with the power distribution network, it becomes of great importance to include load uncertainty in predictive computational tools.
Giambattista Gruosso, Giancarlo Storti Gajani, Zheng Zhang, Luca Daniel, Paolo Maffezzoni   +4 more
doaj   +1 more source

Uncertainty quantification of model predictive control for nonlinear systems with parametric uncertainty using hybrid pseudo-spectral method

Cogent Engineering, 2019
In this paper, a hybrid pseudo-spectral (hPS) method is utilized to analyze the uncertainty of the model predictive control (MPC) for nonlinear systems with stochastic parameter uncertainty.
Ali Namadchian, Mehdi Ramezani
doaj   +1 more source

Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos

, 2017
In this work, the Uncertainty Quantification (UQ) approaches combined systematically to analyze and identify systems. The generalized Polynomial Chaos (gPC) expansion is applied to reduce the computational effort.
Janya-anurak, Chettapong
core   +2 more sources

Evaluation and implementation of measurement uncertainty for determining stationary source emissions: a review

TecnoLógicas, 2018
This paper presents a review of commonly-cited methods for estimating uncertainty in the literature. One of them is the non-stochastic approach proposed by the Guide to the Expression of Uncertainty in Measurement (GUM), which provides an estimation ...
Jhon J. Cárdenas-Monsalve, Andrés F. Ramírez-Barrera, Edilson Delgado-Trejos   +2 more
doaj   +1 more source