Results 11 to 20 of about 264,379 (313)

Affine forward variance models [PDF]

open access: yesFinance and Stochastics, 2018
We introduce the class of affine forward variance (AFV) models of which both the conventional Heston model and the rough Heston model are special cases. We show that AFV models can be characterized by the affine form of their cumulant generating function, which can be obtained as solution of a convolution Riccati equation.
Gatheral, Jim, Keller-Ressel, Martin
openaire   +3 more sources

Validation data of parallel 3D surface-borehole electromagnetic forward modeling. [PDF]

open access: yesData Brief, 2020
Forward modeling of geophysical electromagnetic fields over large three-dimensional volumes is a heavy computational task that demands effective accelerating strategies. As a solution to this computational challenge, a hybrid parallel computing algorithm
Liu C, Cheng L, Abbassi B.
europepmc   +2 more sources

Neuroelectromagnetic Forward Modeling Toolbox [PDF]

open access: yes2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2008
This paper introduces a Neuroelectromagnetic Forward Modeling Toolbox running under MATLAB (The Mathworks, Inc.) for generating realistic head models from available data (MRI and/or electrode locations) and for solving the forward problem of electro-magnetic source imaging numerically.
Zeynep, Akalin Acar, Scott, Makeig
openaire   +2 more sources

Forward Models in Visuomotor Control [PDF]

open access: yesJournal of Neurophysiology, 2002
In recent years, an increasing number of research projects investigated whether the central nervous system employs internal models in motor control. While inverse models in the control loop can be identified more readily in both motor behavior and the firing of single neurons, providing direct evidence for the existence of forward models is more ...
Biren, Mehta, Stefan, Schaal
openaire   +2 more sources

Compressive imaging with iterative forward models [PDF]

open access: yes2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
We propose a new compressive imaging method for reconstructing 2D or 3D objects from their scattered wave-field measurements. Our method relies on a novel, nonlinear measurement model that can account for the multiple scattering phenomenon, which makes the method preferable in applications where linear measurement models are inaccurate.
Hsiou-Yuan Liu   +4 more
openaire   +2 more sources

Moving Forward: On the Limits of Motor-Based Forward Models

open access: yesTrends in Cognitive Sciences, 2019
The human ability to anticipate the consequences that result from action is an essential building block for cognitive, emotional, and social functioning. A dominant view is that this faculty is based on motor predictions, in which a forward model uses a copy of the motor command to predict imminent sensory action-consequences. Although this account was
Dogge, Myrthel   +2 more
openaire   +4 more sources

Influence of Differences in the Density of Seawater on the Measurement of the Underwater Gravity Gradient

open access: yesSensors, 2023
In preparing gravity gradient reference maps for navigation purposes, researchers have tended to use a constant value for the density of seawater. However, the actual seawater density at a particular location may vary due to the effects of longitude ...
Pengfei Xian   +4 more
doaj   +1 more source

Personalized tDCS for Focal Epilepsy—A Narrative Review: A Data-Driven Workflow Based on Imaging and EEG Data

open access: yesBrain Sciences, 2022
Conventional transcranial electric stimulation(tES) using standard anatomical positions for the electrodes and standard stimulation currents is frequently not sufficiently selective in targeting and reaching specific brain locations, leading to ...
Steven Beumer   +6 more
doaj   +1 more source

A forward-constrained regression algorithm for sparse kernel density estimation [PDF]

open access: yes, 2008
Using the classical Parzen window (PW) estimate as the target function, the sparse kernel density estimator is constructed in a forward-constrained regression (FCR) manner. The proposed algorithm selects significant kernels one at a time, while the leave-
Harris, C. J.   +8 more
core   +1 more source

Research on Joint Parameter Inversion for an Integrated Underground Displacement 3D Measuring Sensor

open access: yesSensors, 2015
Underground displacement monitoring is a key means to monitor and evaluate geological disasters and geotechnical projects. There exist few practical instruments able to monitor subsurface horizontal and vertical displacements simultaneously due to ...
Nanying Shentu   +5 more
doaj   +1 more source

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