Publications de Juri Ranieri | EPFL Graph Search

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A sensor is a device that detects or measures a physical property and records, indicates, or otherwise responds to it. In other words, a sensor allows us to interact with the surrounding environment, by measuring qualitatively or quantitatively a given phe ...

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 ...

Euclidean distance matrices (EDMs) are matrices of the squared distances between points. The definition is deceivingly simple; thanks to their many useful properties, they have found applications in psychometrics, crystallography, machine learning, wireles ...

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 ...

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 ...

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 ...

With technological progress, humans tend to create engineering systems with constantly increasing complexity and higher operational requirements. Many complex systems require the use of a Health Management (HM) solution to ensure safety and enable lifecycl ...

Knowing what amount of radioactive material was released from Fukushima in March 2011 and at what time instants is crucial to assess the risk, the pollution, and to understand the scope of the consequences. Moreover, it could be used in forward simulations ...

Recent methods for localization of microphones in a microphone array exploit sound sources at a priori unknown locations. This is convenient for ad-hoc arrays, as it requires little additional infrastructure. We propose a flexible localization algorithm by ...

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 ...

The reconstruction of a diffusion field, such as temperature, from samples collected by a sensor network is a classical inverse problem and it is known to be ill-conditioned. Previous work considered source models, such as sparse sources, to regularize the ...

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 ...

A method for presenting to a user of a wearable audio device a modified audio scene together with additional information related to the audio scene, comprising: capturing audio signals with a plurality of microphones; outputting an audio signal with a plur ...

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 ...

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 ...

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 ...

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 ...

Sensor networks are commonly deployed to measure data from the environment and accurately estimate certain parameters. However, the number of deployed sensors is often limited by several constraints, such as their cost. Therefore, their locations must be o ...

Juri Ranieri

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Sensing the real world : inverse problems, sparsity and sensor placement

Phase Retrieval for Sparse Signals: Uniqueness Conditions

Euclidean Distance Matrices: Essential Theory, Algorithms and Applications

Sampling and Reconstruction of Time-Varying Atmospheric Emissions

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

Method to determine the distribution of temperature sensors

Optimal Sensor Architecture Selection for Health Management of Complex Systems

The Fukushima Inverse Problem

Relax and Unfold: Microphone Localization with Euclidean Distance Matrices

Super Resolution Phase Retrieval for Sparse Signals

Sampling and reconstructing diffusion fields in presence of aliasing

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

Method and apparatus for presenting to a user of a wearable apparatus additional information related to an audio scene

Near-Optimal Sensor Placement for Linear Inverse Problems

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

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

Sampling and Reconstructing Diffusion Fields with Localized Sources

Near-optimal Sensor Placement for Signals lying in a Union of Subspaces