Publications associées à Piecewise polynomial phase approximation approach for the analysis of reconstructed interference felds in digital holographic interferometry

Publications associées (40)

Convex Computation of Value-at-risk Bounds for Stochastic Processes

This article formulates algorithms to upper-bound the maximum value-at-risk (VaR) of a state function along trajectories of stochastic processes. The VaR is upper bounded by two methods: minimax tail-bounds (Cantelli/Vysochanskij-Petunin) and Expected Shor ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2025

Fourier analysis of near-field patterns generated by propagating polaritons

Giulia Tagliabue

Scattering-type scanning near-field optical microscope (s-SNOM) has become an essential tool to study polaritons—quasiparticles of light coupled to collective charge oscillations—via direct probing of their near field with a spatial resolution far beyond t ...

American Physical Society (APS)2024

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

Subwavelength imaging using a solid-immersion diffractive optical processor

Demetri Psaltis, Niyazi Ulas Dinç, Carlo Gigli

Phase imaging is widely used in biomedical imaging, sensing, and material characterization, among other fields. However, direct imaging of phase objects with subwavelength resolution remains a challenge. Here, we demonstrate subwavelength imaging of phase ...

Springernature2024

Estimation and control under uncertainty with application to power systems

Jean-Sébastien Hubert Brouillon

The transition to sustainable energy demands a fundamental redesign of the electrical grid, especially at the distribution level. With the increasing deployment of distributed energy resources, the development of reliable models, accurate state estimation ...

EPFL2024

OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions

Michel Bierlaire, Timothy Michael Hillel, Janody Pougala

Activity-based models offer the potential of a far deeper understanding of daily mobility behaviour than trip-based models. However, activity-based models used both in research and practice have often relied on applying sequential choice models between sub ...

2023

Computationally Efficient Synchrophasor Estimation: Delayed In-Quadrature Interpolated DFT

Mario Paolone, Cesar Garcia Veloso

The paper proposes a synchropahsor estimation (SE) algorithm that leverages the use of a delayed in-quadrature complex signal to mitigate the self-interference of the fundamental tone. The estimator, which uses a three-point IpDFT combined with a three-cyc ...

2024

Timing and spatial selection bias in rapid extreme event attribution

Anthony Christopher Davison, Ophélia Mireille Anna Miralles

Selection bias may arise when data have been chosen in a way that subsequent analysis does not account for. Such bias can arise in climate event attribution studies that are performed rapidly after a devastating "trigger event'', whose occurrence correspon ...

ELSEVIER2023

Optimizing Quantum Compilers: Efficient and Effective Algorithms

Fereshte Mozafari Ghoraba

Quantum computing has made significant progress in recent years, with Google and IBM releasing quantum computers with 72 and 50 qubits, respectively. Google has also achieved quantum supremacy with its 54-qubit device, and IBM has announced the release of ...

EPFL2023

The elliptical Ornstein-Uhlenbeck process

Sofia Charlotta Olhede

We introduce the elliptical Ornstein-Uhlenbeck (OU) process, which is a generalisation of the well-known univariate OU process to bivariate time series. This process maps out elliptical stochastic oscillations over time in the complex plane, which are obse ...

INT PRESS BOSTON, INC2023

A Correlation-Based Electromagnetic Time Reversal Technique to Locate Indoor Transient Radiation Sources

Farhad Rachidi-Haeri, Marcos Rubinstein, Zhaoyang Wang, Qi Li

To overcome the multipath interference in locating transient electromagnetic (EM) radiation sources in an indoor environment, we propose a criterion that calculates the correlation between back-propagated signals from observation points, to be used in EM t ...

Institute of Electrical and Electronics Engineers2021

Minimal regret state estimation of time-varying systems

Giancarlo Ferrari Trecate, Jean-Sébastien Hubert Brouillon

Kalman and H-infinity filters, the most popular paradigms for linear state estimation, are designed for very specific specific noise and disturbance patterns, which may not appear in practice. State observers based on the minimization of regret measures ar ...

Elsevier2023

Experimental assessment of traffic density estimation at link and network level with sparse data

Nikolaos Geroliminis

This paper investigates the accuracy of mean density estimation from direct sensing at link and network levels. Different calculation methods are compared depending on sensor type, probe vehicles or loop detectors, and availability to quantify the magnitud ...

TAYLOR & FRANCIS LTD2022

Retraction-based numerical methods for continuation, interpolation and time integration on manifolds

Axel Elie Joseph Séguin

The goal of this thesis is the development and the analysis of numerical methods for problems where the unknown is a curve on a smooth manifold. In particular, the thesis is structured around the three following problems: homotopy continuation, curve inter ...

EPFL2023

SiML: Sieved Maximum Likelihood for Array Signal Processing

Paul Hurley, Matthieu Martin Jean-André Simeoni

Stochastic Maximum Likelihood (SML) is a popular direction of arrival (DOA) estimation technique in array signal processing. It is a parametric method that jointly estimates signal and instrument noise by maximum likelihood, achieving excellent statistical ...

2021

Versatile shaping of optical frequency combs and applications

Jianqi Hu

Optical frequency combs are a series of phase-locked and equidistant laser lines in the spectral domain. In the time domain, they correspond to periodic pulse trains by the Fourier relation. The ability to shape optical combs and pulse trains is pivotal to ...

EPFL2021

Fourier Sampling in Signal Processing and Numerical Linear Algebra

Amir Zandieh

This thesis focuses on developing efficient algorithmic tools for processing large datasets. In many modern data analysis tasks, the sheer volume of available datasets far outstrips our abilities to process them. This scenario commonly arises in tasks incl ...

EPFL2020

Iterative Bayesian Monte Carlo for nuclear data evaluation

Mathieu Hursin

In this work, we explore the use of an iterative Bayesian Monte Carlo (iBMC) method for nuclear data evaluation within a TALYS Evaluated Nuclear Data Library (TENDL) framework. The goal is to probe the model and parameter space of the TALYS code system to ...

2022

Parameter Estimation of Three-Phase Untransposed Short Transmission Lines from Synchrophasor Measurements

Mario Paolone, Jean-Yves Le Boudec, Arpan Mukhopadhyay

We present a new approach for estimating the parameters of three-phase untransposed electrically short transmission lines using voltage/current synchrophasor measurements obtained from phasor measurement units. The parameters to be estimated are the entrie ...

2020

Practical Compilation of Quantum Programs

Bruno Schmitt Antunes

It's been a little more than 40 years since researchers first suggested exploiting quantum physics to build more powerful computers. During this time, we have seen the development of many quantum algorithms and significant technological advances to make th ...

EPFL2022