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Adaptive sparse grid algorithms with applications to electromagnetic scattering under uncertainty

Related publications (43)

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The SURE-LET approach to image denoising

Florian Luisier

Denoising is an essential step prior to any higher-level image-processing tasks such as segmentation or object tracking, because the undesirable corruption by noise is inherent to any physical acquisition device. When the measurements are performed by phot ...

EPFL2010

Space-time adaptive algorithms for parabolic problems

Virabouth Prachittham

We developed a space and time adaptive method to simulate electroosmosis and mass transport of a sample concentration within a network of microchannels. The space adaptive criteria is based on an error estimator derived using anisotropic interpolation esti ...

EPFL2009

An anisotropic sparse grid stochastic collocation method for partial differential equations with random input data

Fabio Nobile

This work proposes and analyzes an anisotropic sparse grid stochastic collocation method for solving partial differential equations with random coefficients and forcing terms ( input data of the model). The method consists of a Galerkin approximation in th ...

Society for Industrial and Applied Mathematics2008

A sparse grid stochastic collocation method for partial differential equations with random input data

Fabio Nobile

This work proposes and analyzes a Smolyak-type sparse grid stochastic collocation method for the approximation of statistical quantities related to the solution of partial differential equations with random coeffcients and forcing terms ( input data of the ...

Society for Industrial and Applied Mathematics2008

Pseudo Random Numbers Generators available as Web Services

Sébastien Rumley

Series of Pseudo Random Numbers are often used as simulation input, and they strongly Influence the results. Thus, their usage and the usage of their generator need to be taken care of very well. Qualified generators are available on the web as source code ...

Soc Computer Simulation Int, Po Box 17900, San Diego, Ca 92177 Usa2008

A stochastic collocation method for elliptic partial differential equations with random input data

Fabio Nobile

In this paper we propose and analyze a stochastic collocation method to solve elliptic partial differential equations with random coefficients and forcing terms ( input data of the model). The input data are assumed to depend on a finite number of random v ...

Society for Industrial and Applied Mathematics2007

High-order collocation methods for differential equations with random inputs

Jan Sickmann Hesthaven

Recently there has been a growing interest in designing efficient methods for the solution of ordinary/ partial differential equations with random inputs. To this end, stochastic Galerkin methods appear to be superior to other nonsampling methods and, in m ...

SIAM PUBLICATIONS2005

Electromagnetic scattering of high-permittivity particles on a substrate

Olivier Martin

We contribute to the study of the optical properties of high-permittivity nanostructures deposited on surfaces. We present what we believe is anew computational technique derived from the coupled-dipole approximation (CDA), which can accommodate high-permi ...

Optical Society of America2001

Validity domain and limitation of non-retarded Green's tensor for electromagnetic scattering at surfaces

Olivier Martin

This work gives a detailed derivation of the non-retarded dyadic Green's tensor associated with surfaces in the quasistatic approximation. The derivation is made from a rigorous model where the dyadic is expressed as Sommerfeld integrals. We then assess th ...

Elsevier2000

Computational alternatives to random number generators

Serge Vaudenay

We present a simple method for generating random-based signatures when random number generators are either unavailable or of suspected quality (malicious or accidental). In opposition to all past state-machine models, we assume that the signer is a memoryl ...

1999