Publications related to Localizing Unsynchronized Sensors With Unknown Sources

Non-local Functionals Related to the Total Variation and Connections with Image Processing

We present new results concerning the approximation of the total variation,

\int_{\Omega} |\nabla u|

, of a function

u

by non-local, non-convex functionals of the form $$ \Lambda_\delta u = \int_{\Omega} \int_{\Omega} \frac{\delta \varphi \big( |u(x) - ...

2018

A Data-Driven Approach to Power Converter Control via Convex Optimization

Alireza Karimi, Achille Nicoletti, Michele Martino

A new model reference data-driven approach is presented for synthesizing controllers for the CERN power converter control system. This method uses the frequency re- sponse function (FRF) of a system in order to avoid the problem of unmodeled dynamics assoc ...

2017

A Data-driven Approach to Robust Control of Multivariable Systems by Convex Optimization

Alireza Karimi, Christoph Manuel Kammer

The frequency-domain data of a multivariable system in different operating points is used to design a robust controller with respect to the measurement noise and multimodel uncertainty. The controller is fully parametrized in terms of matrix polynomial fun ...

2017

Non-convex, non-local functionals converging to the total variation

Hoài-Minh Nguyên

We present new results concerning the approximation of the total variation, integral(Omega)vertical bar del u vertical bar, of a function u by non-local, non-convex functionals of the form Lambda delta(u) = integral(Omega)integral(Omega)delta phi(vertical ...

Elsevier2017

Robust Smith Predictor Design for Time-Delay Systems with H∞ Performance

Alireza Karimi, Achille Nicoletti, Vinicius De Oliveira

A new method for robust fixed-order H∞ controller design for uncertain time-delay systems is presented. It is shown that the H∞ robust performance condition can be represented by a set of convex constraints with respect to the parameters of a linearly para ...

Springer2015

A Data-Driven Approach in Designing RST Controllers with H∞ Performance via Convex Optimization

Alireza Karimi, Achille Nicoletti, Zlatko Emedi

In this paper, a new method for designing robust fixed-order

\mathcal{H}_{\infty}

discrete-time controllers is presented. The controller structure is a two-degree of freedom polynomial controller of the

RST

type. A data-driven approach is implemented f ...

IEEE2015

Energy Efficient Collaborative Beamforming in Wireless Sensor Networks

Energy efficiency is a major design issue in the context of Wireless Sensor Networks (WSN). If the acquired data is to be sent to a far-away base station, collaborative beamforming performed by the sensors may help to distribute the communication load amon ...

Ieee-Inst Electrical Electronics Engineers Inc2014

H∞ smith predictor design for time-delayed MIMO systems via convex optimization

Alireza Karimi, Achille Nicoletti

A new method for robust fixed-order H∞ controller design for uncertain time-delayed MIMO systems is presented. It is shown that the H∞ robust performance condition can be represented by a set of convex constraints with respect to the parameters of a linear ...

IEEE2014

Obstructions to regularity in the classical Monge problem

Maria Colombo

We provide counterexamples to regularity of optimal maps in the classical Monge problem under various assumptions on the initial data. Our construction is based on a variant of the counterexample in [10] to Lipschitz regularity of the monotone optimal map ...

2014

PURIFY: a new approach to radio-interferometric imaging

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

In a recent article series, the authors have promoted convex optimization algorithms for radio-interferometric imaging in the framework of compressed sensing, which leverages sparsity regularization priors for the associated inverse problem and defines a m ...

Wiley-Blackwell2014

Localizing Unsynchronized Sensors With Unknown Sources

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Non-local Functionals Related to the Total Variation and Connections with Image Processing

A Data-Driven Approach to Power Converter Control via Convex Optimization

A Data-driven Approach to Robust Control of Multivariable Systems by Convex Optimization

Non-convex, non-local functionals converging to the total variation

Robust Smith Predictor Design for Time-Delay Systems with H∞ Performance

A Data-Driven Approach in Designing RST Controllers with H∞ Performance via Convex Optimization

Energy Efficient Collaborative Beamforming in Wireless Sensor Networks

H∞ smith predictor design for time-delayed MIMO systems via convex optimization

Obstructions to regularity in the classical Monge problem

PURIFY: a new approach to radio-interferometric imaging

A Data-Driven Approach in Designing RST Controllers with H∞ Performance via Convex Optimization

A Data-Driven Approach to Power Converter Control via Convex Optimization

Non-convex, non-local functionals converging to the total variation

Energy Efficient Collaborative Beamforming in Wireless Sensor Networks

A Data-driven Approach to Robust Control of Multivariable Systems by Convex Optimization

Robust Smith Predictor Design for Time-Delay Systems with H∞ Performance

Non-local Functionals Related to the Total Variation and Connections with Image Processing

PURIFY: a new approach to radio-interferometric imaging

Obstructions to regularity in the classical Monge problem

H∞ smith predictor design for time-delayed MIMO systems via convex optimization