Publication

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Publications associées (29)

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

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

Alexandra Cameron Karpilow

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

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

Olga Fink

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 ...

2023

The thermally activated deformation behaviour of single-crystalline microcast aluminium wires

Andreas Mortensen, Léa Deillon, Suzanne Godelieve Alphonsine Verheyden

A microcasting process is used to produce high aspect ratio ( > 30) monocrystalline pure aluminium wires with a diameter between 14 and 115 mu m. The role of thermal activation in the plastic deformation of these microwires is measured by means of (single) ...

PERGAMON-ELSEVIER SCIENCE LTD2022

An automatized method to determine latencies of motor-evoked potentials under physiological and pathophysiological conditions

Claudia Bigoni, Friedhelm Christoph Hummel, Takuya Morishita, Andéol Geoffroy Cadic-Melchior, Pierre Theopistos Vassiliadis

Background. Latencies of motor evoked potentials (MEPs) can provide insights into the motor neuronal pathways activated by transcranial magnetic stimulation. Notwithstanding its clinical relevance, accurate, unbiased methods to automatize latency detection ...

IOP Publishing Ltd2022

SafeAMC: Adversarial training for robust modulation classification models

Pascal Frossard, Javier Alejandro Maroto Morales

In communication systems, there are many tasks, like modulation classification, for which Deep Neural Networks (DNNs) have obtained promising performance. However, these models have been shown to be susceptible to adversarial perturbations, namely impercep ...

IEEE2022

Graph signal processing tailored for subgraph focus and community structure

Miljan Petrovic

Community structure in graph-modeled data appears in a range of disciplines that comprise network science. Its importance relies on the influence it bears on other properties of graphs such as resilience, or prediction of missing connections. Nevertheless, ...

EPFL2022

Generalised Implicit Neural Representations

Pierre Vandergheynst

We consider the problem of learning implicit neural representations (INRs) for signals on non-Euclidean domains. In the Euclidean case, INRs are trained on a discrete sampling of a signal over a regular lattice. Here, we assume that the continuous signal e ...

2022

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2

Andras Kis, Aleksandra Radenovic, Zhenyu Wang, Guilherme Migliato Marega, Mukesh Kumar Tripathi

Machine learning and signal processing on the edge are poised to influence our everyday lives with devices that will learn and infer from data generated by smart sensors and other devices for the Internet of Things. The next leap toward ubiquitous electron ...

2022

Uncertain Sampling with Certain Priors

Golnooshsadat Elhami

Sampling has always been at the heart of signal processing providing a bridge between the analogue world and discrete representations of it, as our ability to process data in continuous space is quite limited. Furthermore, sampling plays a key part in unde ...

EPFL2021

Characterization of Non-Stationary Signals in Electric Grids: a Functional Dictionary Approach

Mario Paolone, Asja Derviskadic, Guglielmo Frigo, Alexandra Cameron Karpilow

With the expanding role of converter-interfaced distributed energy resources, modern power grids are evolving towards low-inertia networks that are increasingly vulnerable to extreme dynamics. Consequently, advanced signal processing techniques are needed ...

IEEE Institute of Electrical and Electronics Engineers2021

Electrical Signal Modeling in Cochlear Implants. Study of Temperature and Humidity Effects

Maria-Alexandra Paun

The present paper discusses the climatic effects of humidity and temperature on cochlear implant functioning and the quality of the electrical sound signal. MATLAB Simulink simulations were prepared, offering insights into signal behavior under such climat ...

MDPI2021

Design and Simulation of a Wide-Bandwidth CMUTs Array with Dual-Mixed radii and Multi Operating Modes

Yu Bai, Zhengwen Jiang, Jie Li, Yihe Zhao, Zichen Liu

A capacitive micromachined ultrasonic transducers (CMUTs) array with dual-mixed radii is designed to improve bandwidth and realize multi-modes operating for immersed ultrasonic applications. The two-size (TS) CMUT array is composed of two sub-arrays with d ...

IEEE2021

Planning for a Changing Climate without Accurate Predictions

Parag Rastogi, Mohammad Emtiyaz Khan

Simulation is an informative tool to plan the design and renovation of engineering systems, but its use requires accurate inputs from the users. Inputs such as the unknown future operating conditions might be expected in a system’s lifetime, e.g., the futu ...

Taylor & Francis Group2021

Apparatus and method for locating cells generating an electrical anomaly in a subject's body part

Farhad Rachidi-Haeri

The present invention concerns a data processing apparatus for locating source cells (25) responsible for an electrical anomaly in a subject's body part (8). The apparatus comprises means for: obtaining one or more electrical signals (19) resulting from el ...

2021

Increasing Superstructure Optimization Capacity Through Self-Learning Surrogate Models

François Maréchal, Ivan Daniel Kantor, Julia Granacher

Simulation-based optimization models are widely applied to find optimal operating conditions of processes. Often, computational challenges arise from model complexity, making the generation of reliable design solutions difficult. We propose an algorithm fo ...

2021

On the optimal sampling design for the Graph Total Variation decoder: recovering piecewise-constant graph signals from a few vertex measurements

Rodrigo Cerqueira Gonzalez Pena

Compressed Sensing teaches us that measurements can be traded for offline computation if the signal being sensed has a simple enough representation. Proper decoders can exactly recover the high-dimensional signal of interest from a lower-dimensional vector ...

EPFL2020

An Event-Based System for Low-Power ECG QRS Complex Detection

David Atienza Alonso, Silvio Zanoli, Tomas Teijeiro Campo, Fabio Montagna

One of the greatest challenges in the design of modern wearable devices is energy efficiency. While data processing and communication have received a lot of attention from the industry and academia, leading to highly efficient microcontrollers and transmis ...

IEEE2020

CPGD: Cadzow Plug-and-Play Gradient Descent for Generalised FRI

Martin Vetterli, Paul Hurley, Adrien Georges Jean Besson, Matthieu Martin Jean-André Simeoni

Finite rate of innovation (FRI) is a powerful reconstruction framework enabling the recovery of sparse Dirac streams from uniform low-pass filtered samples. An extension of this framework, called generalised FRI (genFRI), has been recently proposed for han ...

2020

Accelerated MP2RAGE imaging using Cartesian phyllotaxis readout and compressed sensing reconstruction

Jean-Philippe Thiran, Reto Meuli, Tobias Kober, Tom Hilbert

Purpose MP2RAGE T-1-weighted imaging has been shown to be beneficial for various applications, mainly because of its good grey-white matter contrast, its B-1-robustness and ability to derive T(1)maps. Even using parallel imaging, the method requires long a ...

WILEY2020