Publications related to Role of sampling in evaluating classical time autocorrelation functions

Propagating transport-code input parameter uncertainties with deterministic sampling

Olivier Sauter, Ambrogio Fasoli, Basil Duval, Stefano Coda, Jonathan Graves, Yves Martin, Duccio Testa, Patrick Blanchard, Alessandro Pau, Cristian Sommariva, Henri Weisen, Richard Pitts, Yann Camenen, Jan Horacek, Javier García Hernández, Marco Wischmeier, Nicola Vianello, Mikhail Maslov, Federico Nespoli, Yao Zhou, David Pfefferlé, Davide Galassi, Antonio José Pereira de Figueiredo, Jonathan Marc Philippe Faustin, Liang Yao, Dalziel Joseph Wilson, Hamish William Patten, Samuel Lanthaler, Bernhard Sieglin, Otto Asunta

A novel approach to uncertainty quantification in codes simulating fusion plasma, deterministic sampling (DS), is evaluated. This method uses a few carefully selected samples and can be used to propagate input parameter uncertainties through calculations w ...

2018

Shapes from Pixels

Mitra Fatemi

In today's digital world, sampling is at the heart of any signal acquisition device. Imaging devices are ubiquitous examples that capture two-dimensional visual signals and store them as the pixels of discrete images. The main concern is whether and how th ...

EPFL2016

MATHICSE Technical Report : A continuation multi level Monte Carlo (C-MLMC) method for uncertainty quantification in compressible aerodynamics

Fabio Nobile, Pénélope Leyland, Michele Pisaroni

In this work we apply the Continuation Multi-Level Monte Carlo (C-MLMC) algorithm proposed by [Collier et al, BIT 2014] to efficiently propagate operational and geometrical uncertainties in compressible aerodynamics numerical simulations. The key idea of M ...

MATHICSE2016

Sampling-Based Nuclear Data Uncertainty Quantification for Continuous Energy Monte Carlo Codes

Ting Zhu

The goal of the present PhD research is to establish a methodology of nuclear data uncertainty quantification (NDUQ) for MCNPX, the continuous-energy Monte-Carlo (M-C) code. The high fidelity (continuous-energy treatment and flexible geometry modelling) of ...

EPFL2015

Random sampling of bandlimited signals on graphs

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

We study the problem of sampling

k

-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at random. The first strategy is non-adaptive, \ie, independent of the graph structure, and its perform ...

2015

Generalized Poisson Summation Formula for Tempered Distributions

Michaël Unser, Quy Ha Nguyen

The Poisson summation formula (PSF), which relates the sampling of an analog signal with the periodization of its Fourier transform, plays a key role in the classical sampling theory. In its current forms, the formula is only applicable to a limited class ...

IEEE2015

On the Unique Identification of Continuous-Time Autoregressive Models From Sampled Data

Michaël Unser, John Paul Ward, Hagay Kirshner

In this work, we investigate the relationship between continuous-time autoregressive (AR) models and their sampled version. We consider uniform sampling and derive criteria for uniquely determining the continuous-time parameters from sampled data; the mode ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Metropolis-Hastings sampling of paths

Michel Bierlaire, Gunnar Flötteröd

We consider the previously unsolved problem of sampling paths according to a given distribution from a general network. The problem is difficult because of the combinatorial number of alternatives, which prohibits a complete enumeration of all paths and he ...

2013

Identification of Rational Transfer Functions from Sampled Data

Michaël Unser, John Paul Ward, Hagay Kirshner

We consider the task of estimating an operator from sampled data. The operator, which is described by a rational transfer function, is applied to continuous-time white noise and the resulting continuous-time process is sampled uniformly. The main question ...

SampTA2013

Multisensor Change Detection with Nonlinear Canonical Correlation

Devis Tuia, Frank Grégoire Jean de Morsier

The analysis of multi-modal and multi-sensor images is nowadays of paramount importance for Earth Observation (EO) applications. There exist a variety of methods that aim at fusing the different sources of information to obtain a compact representation of ...

2013

Role of sampling in evaluating classical time autocorrelation functions

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Propagating transport-code input parameter uncertainties with deterministic sampling

Shapes from Pixels

MATHICSE Technical Report : A continuation multi level Monte Carlo (C-MLMC) method for uncertainty quantification in compressible aerodynamics

Sampling-Based Nuclear Data Uncertainty Quantification for Continuous Energy Monte Carlo Codes

Random sampling of bandlimited signals on graphs

Generalized Poisson Summation Formula for Tempered Distributions

On the Unique Identification of Continuous-Time Autoregressive Models From Sampled Data

Metropolis-Hastings sampling of paths

Identification of Rational Transfer Functions from Sampled Data

Multisensor Change Detection with Nonlinear Canonical Correlation

MATHICSE Technical Report : A continuation multi level Monte Carlo (C-MLMC) method for uncertainty quantification in compressible aerodynamics

Sampling-Based Nuclear Data Uncertainty Quantification for Continuous Energy Monte Carlo Codes

Multisensor Change Detection with Nonlinear Canonical Correlation

Metropolis-Hastings sampling of paths

Generalized Poisson Summation Formula for Tempered Distributions

Shapes from Pixels

Random sampling of bandlimited signals on graphs

Identification of Rational Transfer Functions from Sampled Data

On the Unique Identification of Continuous-Time Autoregressive Models From Sampled Data

Propagating transport-code input parameter uncertainties with deterministic sampling