Publications related to Sampling error

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 Sparse Signals on the Sphere: Algorithms and Applications

Yue Lu, Ivan Dokmanic

We propose a sampling scheme that can perfectly reconstruct a collection of spikes on the sphere from samples of their lowpass-filtered observations. Central to our algorithm is a generalization of the annihilating filter method, a tool widely used in arra ...

Institute of Electrical and Electronics Engineers2016

Attributing Aliasing Artifacts in Dirty Intensity Fields to their Parent Source

Matthieu Martin Jean-André Simeoni

Estimating intensity fields of stochastic phenomenons is of crucial interest in many scientific applications. Typical experimental setups involve an acquisition system, that subsequently filters and samples the probed intensity field. This equivalently def ...

2016

On Selection of Samples in Algebraic Attacks and a New Technique to Find Hidden Low Degree Equations

Serge Vaudenay, Pouyan Sepehrdad, Petr Susil

The best way of selecting samples in algebraic attacks against block ciphers is not well explored and understood. We introduce a simple strategy for selecting the plaintexts and demonstrate its strength by breaking reduced-round KATAN, LBLOCK and SIMON. Fo ...

Springer Verlag2016

Locally differentially-private distribution estimation

Michael Christoph Gastpar, Adriano Pastore

We consider a setup in which confidential i.i.d. samples X1, ..., Xn from an unknown discrete distribution PX are passed through a discrete memoryless privatization channel (a.k.a. mechanism) which guarantees an epsilon-level of local differential privacy. ...

Ieee2016

Sampling and Reconstruction of Shapes with Algebraic Boundaries

Martin Vetterli, Arash Amini, Mitra Fatemi

We present a sampling theory for a class of binary images with finite rate of innovation (FRI). Every image in our model is the restriction of

\mathds{1}_{\{p\leq0\}}

to the image plane, where

\mathds{1}

denotes the indicator function and

p

is some r ...

2016

Influence of loading history on mechanical properties of biomaterials

Tom Charles Maurice Walet

It is known that the mechanical response to load or displacement of a biological tissue can highly vary from one cycle to the next. Therefore, in order to establish a reference state for repeating data measurements, tissues are subjected to a preliminary s ...

2016

How does one compute the noise power to simulate real and complex GNSS signals?

Cyril Botteron, Jérôme Leclère

Simulation of GNSS signals is very important to test and validate algorithms. With some algorithms, such as acquisition or tracking, we do not need to simulate a realistic constellation with actual ranges, Doppler or navigation data. We can simply simulate ...

2016

Gender differences in visual perception

Michael Herzog, Christine Mohr, Maya Roinishvili

Gender differences are well established in cognition and somato-sensation, but there are almost no studies on gender differences in visual perception. One reason is that sample size is often small because effect sizes are large. Small samples are not well ...

2016

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

Sampling error

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

Sampling Sparse Signals on the Sphere: Algorithms and Applications

Attributing Aliasing Artifacts in Dirty Intensity Fields to their Parent Source

On Selection of Samples in Algebraic Attacks and a New Technique to Find Hidden Low Degree Equations

Locally differentially-private distribution estimation

Sampling and Reconstruction of Shapes with Algebraic Boundaries

Influence of loading history on mechanical properties of biomaterials

How does one compute the noise power to simulate real and complex GNSS signals?

Gender differences in visual perception

Shapes from Pixels

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

How does one compute the noise power to simulate real and complex GNSS signals?

Sampling Sparse Signals on the Sphere: Algorithms and Applications

Attributing Aliasing Artifacts in Dirty Intensity Fields to their Parent Source

Locally differentially-private distribution estimation

On Selection of Samples in Algebraic Attacks and a New Technique to Find Hidden Low Degree Equations

Sampling and Reconstruction of Shapes with Algebraic Boundaries

Influence of loading history on mechanical properties of biomaterials

Gender differences in visual perception

Shapes from Pixels