Publications related to A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms

MULAN: A Blind and Off-Grid Method for Multichannel Echo Retrieval

This paper addresses the general problem of blind echo retrieval, i.e., given M sensors measuring in the discrete-time domain M mixtures of K delayed and attenuated copies of an unknown source signal, can the echo locations and weights be recovered? This p ...

2018

MULAN: A Blind and Off-Grid Method for Multichannel Echo Retrieval

Rémi Gribonval, Helena Peic Tukuljac

This paper addresses the general problem of blind echo retrieval, i.e., given M sensors measuring in the discrete-time domain M mixtures of K delayed and attenuated copies of an unknown source signal, can the echo locations and weights be recovered? This p ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

Method for estimating synchrophasors during static and dynamic conditions

Mario Paolone, Asja Derviskadic, Paolo Romano

A method for performing synchrophasor estimation of an input signal, whereby the input signal is a sinusoidal power system voltage or current signal, comprising: a. Periodic sampling of a continuous time-domain waveform, consisting of a power system voltag ...

2018

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Jean-Philippe Thiran, Martin Vetterli, Dimitris Perdios, Eric Bezzam, Adrien Georges Jean Besson, Hanjie Pan

In this paper we show that it is sufficient to recover the locations of K strong reflectors within an insonified medium from three receive elements and 2K+1 samples per element. The proposed approach leverages advances in sampling signals with a finite rat ...

IEEE2018

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Jean-Philippe Thiran, Martin Vetterli, Dimitris Perdios, Eric Bezzam, Adrien Besson, Hanjie Pan

In this paper we show that it is sufficient to recover the locations of K strong reflectors within an insonified medium from three receive elements and 2K+1 samples per element. The proposed approach leverages advances in sampling signals with a finite rat ...

IEEE2018

Towards Generalized FRI Sampling with an Application to Source Resolution in Radioastronomy

Martin Vetterli, Thierry Blu, Hanjie Pan

It is a classic problem to estimate continuous-time sparse signals, like point sources in a direction-of-arrival problem, or pulses in a time-of-flight measurement. The earliest occurrence is the estimation of sinusoids in time series using Prony's method. ...

Institute of Electrical and Electronics Engineers2017

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Volkan Cevher, Mikhail Kapralov, Jonathan Mark Scarlett, Amir Zandieh

The problem of approximately computing the

k

dominant Fourier coefficients of a vector

X

quickly, and using few samples in time domain, is known as the Sparse Fourier Transform (sparse FFT) problem. A long line of work on the sparse FFT has resulted in ...

2017

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

Kyong Hwan Jin

While the recent theory of compressed sensing provides an opportunity to overcome the Nyquist limit in recovering sparse signals, a solution approach usually takes the form of an inverse problem of an unknown signal, which is crucially dependent on specifi ...

IEEE2017

Sparse inverse problems for Fourier imaging

Anna Auria Rasclosa

Many natural images have low intrinsic dimension (a.k.a. sparse), meaning that they can be represented with very few coefficients when expressed in an adequate domain. The recent theory of Compressed Sensing exploits this property offering a powerful frame ...

EPFL2017

Towards Stationary Time-Vertex Signal Processing

Pierre Vandergheynst, Nathanaël Perraudin, Andreas Loukas, Francesco Grassi

Graph-based methods for signal processing have shown promise for the analysis of data exhibiting irregular structure, such as those found in social, transportation, and sensor networks. Yet, though these systems are often dynamic, state-of-the-art methods ...

Ieee2017

A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms

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MULAN: A Blind and Off-Grid Method for Multichannel Echo Retrieval

MULAN: A Blind and Off-Grid Method for Multichannel Echo Retrieval

Method for estimating synchrophasors during static and dynamic conditions

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Towards Generalized FRI Sampling with an Application to Source Resolution in Radioastronomy

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

Sparse inverse problems for Fourier imaging

Towards Stationary Time-Vertex Signal Processing

MULAN: A Blind and Off-Grid Method for Multichannel Echo Retrieval

MULAN: A Blind and Off-Grid Method for Multichannel Echo Retrieval

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Towards Generalized FRI Sampling with an Application to Source Resolution in Radioastronomy

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

Sparse inverse problems for Fourier imaging

Method for estimating synchrophasors during static and dynamic conditions

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Towards Stationary Time-Vertex Signal Processing