Results 61 to 70 of about 12,137 (169)

A Near-Optimal Sampling Strategy for Sparse Recovery of Polynomial Chaos Expansions

, 2017
Compressive sampling has become a widely used approach to construct polynomial chaos surrogates when the number of available simulation samples is limited.
Alemazkoor, Negin, Meidani, Hadi
core   +1 more source

Uncertainpy: A Python Toolbox for Uncertainty Quantification and Sensitivity Analysis in Computational Neuroscience

Frontiers in Neuroinformatics, 2018
Computational models in neuroscience typically contain many parameters that are poorly constrained by experimental data. Uncertainty quantification and sensitivity analysis provide rigorous procedures to quantify how the model output depends on this ...
Simen Tennøe, Simen Tennøe, Geir Halnes, Geir Halnes, Gaute T. Einevoll, Gaute T. Einevoll, Gaute T. Einevoll   +6 more
doaj   +1 more source

Computing derivative-based global sensitivity measures using polynomial chaos expansions [PDF]

, 2014
In the field of computer experiments sensitivity analysis aims at quantifying the relative importance of each input parameter (or combinations thereof) of a computational model with respect to the model output uncertainty.
B. Sudret, B. Sudret, C. V. Mai, C. V. Mai   +3 more
core  

Some Notes to Extend the Study on Random Non-Autonomous Second Order Linear Differential Equations Appearing in Mathematical Modeling

Mathematical and Computational Applications, 2018
The objective of this paper is to complete certain issues from our recent contribution (Calatayud, J.; Cortés, J.-C.; Jornet, M.; Villafuerte, L. Random non-autonomous second order linear differential equations: mean square analytic solutions and their ...
Julia Calatayud Gregori, Juan Carlos Cortés López, Marc Jornet Sanz   +2 more
doaj   +1 more source

Distributional uncertainty analysis using polynomial chaos expansions [PDF]

2010 IEEE International Symposium on Computer-Aided Control System Design, 2010
A computationally efficient approach is presented that quantifies the influence of parameter uncertainties on the states and outputs of finite-time control trajectories for nonlinear systems, based on the approximate representation of the model via polynomial chaos expansion.
Zoltan K. Nagy, Richard D. Braatz
openaire   +1 more source

Stochastic Optimization using Polynomial Chaos Expansions

, 2020
Polynomial chaos based methods enable the efficient computation of output variability in the presence of input uncertainty in complex models. Consequently, they have been used extensively for propagating uncertainty through a wide variety of physical systems.
openaire   +2 more sources

Polynomial-Chaos-based Kriging

, 2015
Computer simulation has become the standard tool in many engineering fields for designing and optimizing systems, as well as for assessing their reliability.
Schoebi, R., Sudret, B., Wiart, J.
core   +1 more source

Deep Polynomial Chaos Expansion

Polynomial chaos expansion (PCE) is a classical and widely used surrogate modeling technique in physical simulation and uncertainty quantification. By taking a linear combination of a set of basis polynomials - orthonormal with respect to the distribution of uncertain input parameters - PCE enables tractable inference of key statistical quantities ...
Exenberger, Johannes, Ranftl, Sascha, Peharz, Robert   +2 more
openaire   +2 more sources

Finite pseudo orbit expansions for spectral quantities of quantum graphs

, 2012
We investigate spectral quantities of quantum graphs by expanding them as sums over pseudo orbits, sets of periodic orbits. Only a finite collection of pseudo orbits which are irreducible and where the total number of bonds is less than or equal to the ...
Berkolaiko G, Berkolaiko G, Berry M V, Bogomolny E, C H Joyner, Comtet A, Desbois J, Edmunds D E, Gutzwiller M, Haake F, Harmer M, Harrison J M, Harrison J M, Harrison J M, Harrison J M, Harrison J M, J M Harrison, Keating J P, Kirsten K, Kostrykin V, R Band, Roth J P, Rueckriemen R, Tanner G, Tanner G   +24 more
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Analysis of inductive power transfer systems by metamodeling techniques

Comptes Rendus. Physique
This paper presents some metamodeling techniques to analyze the variability of the performances of an inductive power transfer (IPT) system, considering the sources of uncertainty (misalignment between the coils, the variation in air gap, and the ...
Pei, Yao, Pichon, Lionel, Bensetti, Mohamed, Le Bihan, Yann   +3 more
doaj   +1 more source