Impact of uncertain head tissue conductivity in the optimization of transcranial direct current stimulation for an auditory target
Objective. Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation
technique to modify neural excitability. Using multi-array tDCS, we investigate the influence …
technique to modify neural excitability. Using multi-array tDCS, we investigate the influence …
The influence of random element displacement on DOA estimates obtained with (Khatri–Rao-) root-MUSIC
V Inghelbrecht, J Verhaevert, T Van Hecke, H Rogier - Sensors, 2014 - mdpi.com
Although a wide range of direction of arrival (DOA) estimation algorithms has been
described for a diverse range of array configurations, no specific stochastic analysis …
described for a diverse range of array configurations, no specific stochastic analysis …
[PDF][PDF] Improving EEG Electrode Sensitivity with Graphene Nano Powder and Neural Network for Schizophrenia Diagnosis
V Divya, SS Kumar, S Usha, S Hemamalini… - Tikrit Journal of …, 2023 - iasj.net
Nadu, India., b Department of Electrical and Electronics Engineering, SA Engineering
College, Chennai, Tamil Nadu, India., c Department of AIDS, Rajalakshmi Institute of …
College, Chennai, Tamil Nadu, India., c Department of AIDS, Rajalakshmi Institute of …
[HTML][HTML] Bayesian inference in the uncertain EEG problem including local information and a sensor correlation matrix
RH De Staelen, G Crevecoeur, T Goessens… - … of Computational and …, 2013 - Elsevier
We present a framework based on Bayesian inference to combine expert judgment and the
problem of an uncertain conductivity in the electroencephalography (EEG) inverse problem …
problem of an uncertain conductivity in the electroencephalography (EEG) inverse problem …
Sensitivity analysis and variance reduction in a stochastic non-destructive testing problem
RH De Staelen, K Beddek - International Journal of Computer …, 2015 - Taylor & Francis
In this paper, we present a framework to deal with uncertainty quantification in case where
the ranges of variability of the random parameters are ill-known. Namely the physical …
the ranges of variability of the random parameters are ill-known. Namely the physical …
[PDF][PDF] Original Research Sensitivity Analysis and Variance Reduction in a Stochastic NDT Problem
RH De Staelena, K Beddekb - academia.edu
In this paper, we present a framework to deal with uncertainty quantification in case where
the ranges of variability of the random parameters are ill-known. Namely the physical …
the ranges of variability of the random parameters are ill-known. Namely the physical …
[HTML][HTML] On cost function transformations for the reduction of uncertain model parameters' impact towards the optimal solutions
G Crevecoeur, RH De Staelen - Journal of computational and applied …, 2015 - Elsevier
Uncertainties affect the accuracy of nonlinear static or dynamic optimization and inverse
problems. The propagation of uncertain model parameters towards the optimal problem …
problems. The propagation of uncertain model parameters towards the optimal problem …