Publications related to Sampling signals with finite rate of innovation

PCA using graph total variation

Pierre Vandergheynst, Nathanaël Perraudin, Benjamin Ricaud, Nauman Shahid, Vasilis Kalofolias

Mining useful clusters from high dimensional data has received sig- nificant attention of the signal processing and machine learning com- munity in the recent years. Linear and non-linear dimensionality reduction has played an important role to overcome th ...

Ieee2016

Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

Jean-Philippe Thiran, Yves Wiaux, Rafael Eduardo Carrillo Rangel, Adrien Georges Jean Besson, Olivier Bernard

The theory of compressed sensing (CS) leverages upon structure of signals in order to reduce the number of samples needed to reconstruct a signal, compared to the Nyquist rate. Although CS approaches have been proposed for ultrasound (US) imaging with prom ...

Ieee2016

Sampling strategies and post-processing methods for increasing the time resolution of organic aerosol measurements requiring long sample-collection times

Satoshi Takahama, Robin Lewis Modini

The composition and properties of atmospheric organic aerosols (OAs) change on timescales of minutes to hours. However, some important OA characterization techniques typically require greater than a few hours of sample-collection time (e.g., Fourier transf ...

Copernicus GmbH2016

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

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

Riemannian Optimization For High-Dimensional Tensor Completion

Michael Maximilian Steinlechner

Tensor completion aims to reconstruct a high-dimensional data set where the vast majority of entries is missing. The assumption of low-rank structure in the underlying original data allows us to cast the completion problem into an optimization problem rest ...

Siam Publications2016

Learning Data Triage: Linear Decoding Works for Compressive MRI

Volkan Cevher, Yen-Huan Li

The standard approach to compressive sampling considers recovering an unknown deterministic signal with certain known structure, and designing the sub-sampling pattern and recovery algorithm based on the known structure. This approach requires looking for ...

Ieee2016

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

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

Tutorial: Sub-Nyquist artifacts and sampling moiré effects

Isaac Amidror

Sampling moiré effects are well known in signal processing. They occur when a continuous periodic signal g(x) is sampled using a sampling frequency fs that does not respect the Nyquist condition, and the signal frequency f folds-over and gives a new, false ...

The Royal Society Publishing2015

Sampling signals with finite rate of innovation

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PCA using graph total variation

Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

Sampling strategies and post-processing methods for increasing the time resolution of organic aerosol measurements requiring long sample-collection times

Locally differentially-private distribution estimation

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

Riemannian Optimization For High-Dimensional Tensor Completion

Learning Data Triage: Linear Decoding Works for Compressive MRI

Generalized Poisson Summation Formula for Tempered Distributions

Random sampling of bandlimited signals on graphs

Tutorial: Sub-Nyquist artifacts and sampling moiré effects

Learning Data Triage: Linear Decoding Works for Compressive MRI

Generalized Poisson Summation Formula for Tempered Distributions

Random sampling of bandlimited signals on graphs

PCA using graph total variation

Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

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

Sampling strategies and post-processing methods for increasing the time resolution of organic aerosol measurements requiring long sample-collection times

Riemannian Optimization For High-Dimensional Tensor Completion

Tutorial: Sub-Nyquist artifacts and sampling moiré effects

Locally differentially-private distribution estimation