Publications by Amina Chebira | EPFL Graph Search

Super Resolution Phase Retrieval for Sparse Signals

Martin Vetterli, Juri Ranieri, Gilles Baechler, Amina Chebira, Miranda Krekovic

In a variety of fields, in particular those involving imaging and optics, we often measure signals whose phase is missing or has been irremediably distorted. Phase retrieval attempts to recover the phase information of a signal from the magnitude of its Fo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Method, computer program and apparatus for measuring a distribution of a physical variable in a region

Martin Vetterli, Juri Ranieri, Amina Chebira

Method for measuring a distribution of a physical variable in a region, comprising the step of: measuring an average value of the physical variable along each of a plurality of lines in said region; estimating the distribution of the physical variable in s ...

2015

Near-optimal thermal monitoring framework for many-core systems on chip

Martin Vetterli, David Atienza Alonso, Juri Ranieri, Amina Chebira, Alessandro Vincenzi

Chip designers place on-chip thermal sensors to measure local temperatures, thus preventing thermal runaway situations in many-core processing architectures. However, the quality of the thermal reconstruction is directly dependent on the number of placed s ...

Institute of Electrical and Electronics Engineers2015

Method to determine the distribution of temperature sensors

Martin Vetterli, David Atienza Alonso, Juri Ranieri, Amina Chebira, Alessandro Vincenzi

Apparatus comprising M sensors for measuring the temperature on M locations of the apparatus and an estimator configured to estimate a temperature vector of the apparatus with N temperature variables, whereby the estimator is configured to approximate the ...

2014

Near-Optimal Sensor Placement for Linear Inverse Problems

Martin Vetterli, Juri Ranieri, Amina Chebira

A classic problem is the estimation of a set of parameters from measurements collected by only a few sensors. The number of sensors is often limited by physical or economical constraints and their placement is of fundamental importance to obtain accurate e ...

2014

Phase Retrieval for Sparse Signals: Uniqueness Conditions

Martin Vetterli, Yue Lu, Juri Ranieri, Amina Chebira

In a variety of fields, in particular those involving imaging and optics, we often measure signals whose phase is missing or has been irremediably distorted. Phase retrieval attempts the recovery of the phase information of a signal from the magnitude of i ...

2013

Sampling and Reconstruction of Time-Varying Atmospheric Emissions

Martin Vetterli, Ivan Dokmanic, Juri Ranieri, Amina Chebira

We study the spatio-temporal sampling of physical fields representing the dispersion of a substance in the atmosphere. We consider the following setup: N sensors are deployed at ground level and measure the concentration of a particular substance, while M ...

Ieee2012

EigenMaps: Algorithms for Optimal Thermal Maps Extraction and Sensor Placement on Multicore Processors

Martin Vetterli, David Atienza Alonso, Juri Ranieri, Amina Chebira, Alessandro Vincenzi

Chip designers place on-chip sensors to measure local temperatures, thus preventing thermal runaway situations in multicore processing architectures. However, thermal characterization is directly dependent on the number of placed sensors, which should be m ...

ACM2012

Sensor Networks for Diffusion Fields: Detection of Sources in Space and Time

Martin Vetterli, Ivan Dokmanic, Juri Ranieri, Amina Chebira

We consider the problem of reconstructing a diffusion field, such as temperature, from samples collected by a sensor network. Motivated by the fast decay of the eigenvalues of the diffusion equation, we approximate the field by a truncated series. We show ...

2011

Sampling and Reconstructing Diffusion Fields with Localized Sources

Martin Vetterli, Yue Lu, Juri Ranieri, Amina Chebira

We study the spatiotemporal sampling of a diffusion field generated by K point sources, aiming to fully reconstruct the unknown initial field distribution from the sample measurements. The sampling operator in our problem can be described by a matrix deriv ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011