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Localized model order reduction and domain decomposition methods for coupled heterogeneous systems

Publications associées (33)

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We propose a framework that connects the spatial symmetries of a metasurface to its material parameter tensors and its scattering matrix. This provides a simple and universal way to effortlessly determine the properties of a metasurface scattering response ...

SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS2023

Efficient numerical simulations of coupled multi-component systems can be particularly challenging. This is mostly due to the complexity of their solutions, as mutual interactions may cause emergent behaviors, including synchronization and instabilities. V ...

EPFL2023

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In this article, we propose a novel approach for the localization of electromagnetic interference (EMI) sources based on the concept of compressive sensing and metalenses. We show that using the spatial and frequency dispersion offered by the metalens, we ...

2022

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Given an image sequence featuring a portion of a sports field filmed by a moving and uncalibrated camera, such as the one of the smartphones, our goal is to compute automatically in real time the focal length and extrinsic camera parameters for each image ...

2020

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Super-resolution fluorescence microscopy improves spatial resolution, but this comes at a loss of image throughput and presents unique challenges in identifying optimal acquisition parameters. Microscope automation routines can offset these drawbacks, but ...

OPTICAL SOC AMER2018

From Timed Component-Based Systems to Time-Triggered Implementations: A Correct-by-Design Approach

In hard real-time embedded systems, design and specification methods and their associated tools must allow development of temporally deterministic systems to ensure their safety. To achieve this goal, we are specifically interested in methodologies based o ...

CEA LIST2017

Reconstruction of underconstrained tomographic data sets remains a major challenge. Standard analytical techniques frequently lead to unsatisfactory results due to insufficient information. Several iterative algorithms, which can easily integrate a priori ...

IEEE2016

Joint image reconstruction and segmentation using the Potts model

Michaël Unser, Martin Kurt Storath

We propose a new algorithmic approach to the non-smooth and non-convex Potts problem (also called piecewise-constant Mumford-Shah problem) for inverse imaging problems. We derive a suitable splitting into specific subproblems that can all be solved efficie ...

Institute of Physics2015

An Algorithmic Framework for Mumford-Shah Regularization of Inverse Problems in Imaging

Martin Kurt Storath

The Mumford-Shah model is a very powerful variational approach for edge preserving regularization of image reconstruction processes. However, it is algorithmically challenging because one has to deal with a non-smooth and non-convex functional. In this pap ...

Iop Publishing Ltd2015

Probabilistic assessment of the process-noise covariance matrix of discrete Kalman filter state estimation of active distribution networks

Mario Paolone, Marco Pignati, Lorenzo Zanni, Styliani Sarri

The accuracy of state estimators using the Kalman Filter (KF) is largely influenced by the measurement and the process noise covariance matrices. The former can be directly inferred from the available measurement devices whilst the latter needs to be asses ...

IEEE2014