Publications related to Compressed Sensing of Memoryless Sources

Blind Phase Calibration in Sparse Recovery

We consider a blind calibration problem in a compressed sensing measurement system in which each sensor introduces an unknown phase shift to be determined. We show that this problem can be approached similarly to the problem of phase retrieval from quadrat ...

2013

Statistical Models for Querying and Managing Time-Series Data

Saket Sathe

In recent years we are experiencing a dramatic increase in the amount of available time-series data. Primary sources of time-series data are sensor networks, medical monitoring, financial applications, news feeds and social networking applications. Availab ...

EPFL2013

Sparse image reconstruction on the sphere: implications of a new sampling theorem

Jean-Philippe Thiran, Pierre Vandergheynst, Dimitri Nestor Alice Van De Ville, Yves Wiaux, Gilles Puy, Jason Douglas McEwen

A new sampling theorem on the sphere has been developed recently, reducing the number of samples required to represent a band-limited signal by a factor of two for equiangular sampling schemes. For signals sparse in a spatially localised measure, such as i ...

Institute of Electrical and Electronics Engineers2013

Coding schemes for broadcast erasure channels with feedback: the two multicast case

Christina Fragouli, Efe Onaran

We consider the single hop broadcast packet erasure channel (BPEC) with two multicast sessions (each of them destined to a different group of

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users) and regularly available instantaneous receiver ACK/NACK feedback. Using the insight gained from recent ...

2013

Continuous Localization Using Sparsity Constraints for High-Density Super-Resolution Microscopy

Michaël Unser, Cédric René Jean Vonesch, Hagay Kirshner

Super-resolution localization microscopy relies on sparse activation of photo-switchable probes. Such activation, however, introduces limited temporal resolution. High-density imaging overcomes this limitation by allowing several neighboring probes to be a ...

IEEE2013

Optimal Sampling Rates in Infinite-Dimensional Compressed Sensing

Martin Vetterli, Loïc Arnaud Baboulaz, Mitra Fatemi

The theory of compressed sensing studies the problem of recovering a high dimensional sparse vector from its projections onto lower dimensional subspaces. The recently introduced framework of infinite-dimensional compressed sensing [1], to some extent gene ...

2013

Fast and robust estimation of jointly sparse channels

Martin Vetterli, Ali Hormati, Yann Barbotin

A device and method for estimating multipath jointly sparse channels. The method comprises receiving a number K of signal components by a number P of receiving antennas, where P≧2. The method further comprises estimating the sparsity condition of the multi ...

2013

Distributed average consensus with quantization refinement

Pascal Frossard, Ye Pu, Effrosyni Kokiopoulou

We consider the problem of distributed average consensus in a sensor network where sensors exchange quantized information with their neighbors. We propose a novel quantization scheme that exploits the increasing correlation between the values exchanged by ...

Institute of Electrical and Electronics Engineers2013

Proof of the Outage Probability Conjecture for MISO Channels

Emre Telatar, Emmanuel Abbé

It is conjectured that the covariance matrices minimizing the outage probability under a power constraint for multiple-input multiple-output channels with Gaussian fading are diagonal with either zeros or constant values on the diagonal. In the multiple-in ...

Institute of Electrical and Electronics Engineers2013

Sparse Approximation Using M-Term Pursuit and Application in Image and Video Coding

Pascal Frossard, Pierre Vandergheynst, Adel Rahmoune

This paper introduces a novel algorithm for sparse approximation in redundant dictionaries called the M-term pursuit (MTP). This algorithm decomposes a signal into a linear combination of atoms that are selected in order to represent the main signal compon ...

Institute of Electrical and Electronics Engineers2012

Compressed Sensing of Memoryless Sources

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Blind Phase Calibration in Sparse Recovery

Statistical Models for Querying and Managing Time-Series Data

Sparse image reconstruction on the sphere: implications of a new sampling theorem

Coding schemes for broadcast erasure channels with feedback: the two multicast case

Continuous Localization Using Sparsity Constraints for High-Density Super-Resolution Microscopy

Optimal Sampling Rates in Infinite-Dimensional Compressed Sensing

Fast and robust estimation of jointly sparse channels

Distributed average consensus with quantization refinement

Proof of the Outage Probability Conjecture for MISO Channels

Sparse Approximation Using M-Term Pursuit and Application in Image and Video Coding

Continuous Localization Using Sparsity Constraints for High-Density Super-Resolution Microscopy

Statistical Models for Querying and Managing Time-Series Data

Sparse image reconstruction on the sphere: implications of a new sampling theorem

Distributed average consensus with quantization refinement

Coding schemes for broadcast erasure channels with feedback: the two multicast case

Fast and robust estimation of jointly sparse channels

Sparse Approximation Using M-Term Pursuit and Application in Image and Video Coding

Blind Phase Calibration in Sparse Recovery

Optimal Sampling Rates in Infinite-Dimensional Compressed Sensing

Proof of the Outage Probability Conjecture for MISO Channels