Publications associées à Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

Functional-Basis Analysis of Non-Stationary Signals in Modern Power Grids: Theory and Implementation in Embedded Systems

Situational awareness strategies are essential for the reliable and secure operation of the electric power grid which represents critical infrastructure in modern society. With the rise of converter-interfaced renewable generation and the consequent shift ...

EPFL2024

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

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In inverse problems, the task is to reconstruct an unknown signal from its possibly noise-corrupted measurements. Penalized-likelihood-based estimation and Bayesian estimation are two powerful statistical paradigms for the resolution of such problems. They ...

EPFL2024

Unified Harmonic Power-Flow and Stability Analysis of Power Grids with Converter-Interfaced Distributed Energy Resources

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EPFL2024

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In this letter, we introduce an optimal transport framework for inferring power distributions over both spatial location and temporal frequency. Recently, it has been shown that optimal transport is a powerful tool for estimating spatial spectra that chang ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Thermal transport of glasses via machine learning driven simulations

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Accessing the thermal transport properties of glasses is a major issue for the design of production strategies of glass industry, as well as for the plethora of applications and devices where glasses are employed. From the computational standpoint, the che ...

Frontiers Media Sa2024

Vibrational NDT with Under-sampled Data through Physics-informed Neural Networks

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The vibrational response of solid materials and structural components is substantially governed by their mechanical and geometrical properties. Low-frequency vibrations and modal frequencies are sensitive to global geometrical deviations, while high-freque ...

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A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods

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We present a statistical framework to benchmark the performance of reconstruction algorithms for linear inverse problems, in particular, neural-network-based methods that require large quantities of training data. We generate synthetic signals as realizati ...

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A 1-GS/s 6-8-b Cryo-CMOS SAR ADC for Quantum Computing

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This article presents a two-times interleaved, loop-unrolled SAR analog-to-digital converter (ADC) operational from 300 down to 4.2 K. The 6-8-bit resolution and the sampling speed up to 1 GS/s are targeted at digitizing the multi-channel frequency-multipl ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

An optimal preconditioned FFT-accelerated finite element solver for homogenization

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We generalize and provide a linear algebra-based perspective on a finite element (FE) ho-mogenization scheme, pioneered by Schneider et al. (2017)[1] and Leuschner and Fritzen (2018)[2]. The efficiency of the scheme is based on a preconditioned, well-scale ...

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The Sparsity of Cycle Spinning for Wavelet-Based Solutions of Linear Inverse Problems

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The usual explanation of the efficacy of wavelet-based methods hinges on the sparsity of many real-world objects in the wavelet domain. Yet, standard wavelet-shrinkage techniques for sparse reconstruction are not competitive in practice, one reason being t ...

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Exploring the effectiveness of using internal CNC system signals for chatter detection in milling process

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Chatter is a harmful self-excited vibration that commonly occurs during milling processes. Data -driven chatter detection and prediction is critical to achieve high surface quality and process efficiency. Most existing chatter detection approaches are base ...

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Tensor approximation of the self-diffusion matrix of tagged particle processes

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The objective of this paper is to investigate a new numerical method for the approximation of the self-diffusion matrix of a tagged particle process defined on a grid. While standard numerical methods make use of long-time averages of empirical means of de ...

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Adaptive isogeometric methods with C-1 (truncated) hierarchical splines on planar multi-patch domains

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Isogeometric analysis is a powerful paradigm which exploits the high smoothness of splines for the numerical solution of high order partial differential equations. However, the tensor-product structure of standard multivariate B-spline models is not well s ...

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Learned Compressive Representations for Single-Photon 3D Imaging

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Hardware Implementation of Digital Signal Processing Algorithms for Programmable Epilepsy Control Systems

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Computation of the attenuation function of the lightning return-stroke current from electromagnetic fields measured in a short-duration time-window, Part I: Theoretical investigation

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Low-Rank Tensor Methods for High-Dimensional Problems

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Numerical simulation of immiscible incompressible viscous, viscoelastic and elastic multiphase flows

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Rare events include many of the most interesting transformation processes in condensed matter, from phase transitions to biomolecular conformational changes to chemical reactions. Access to the corresponding mechanisms, free-energy landscapes and kinetic r ...

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Region Extraction in Mesh Intersection

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Region extraction is a very common task in both Computer Science and Engineering with several applications in object recognition and motion analysis, among others. Most of the literature focuses on regions delimited by straight lines, often in the special ...

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