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Concept

Non-uniform discrete Fourier transform

Publications associées (32)

Fourier uniqueness and interpolation in Euclidean space

Martin Peter Stoller

We prove that every Schwartz function in Euclidean space can be completely recovered given only its restrictions and the restrictions of its Fourier transform to all origin-centered spheres whose radii are square roots of integers. In particular, the only ...

EPFL2022

Resynchronization of islanded unbalanced ADNs: Control, synchrocheck and experimental validation

Mario Paolone, Sherif Alaa Salaheldin Fahmy

The problem of securely reconnecting active distribution networks (ADNs) - e.g. microgrids - to their upstream grids at the point of common coupling (PCC) has been extensively discussed by the existing literature. The latter is commonly referred to as resy ...

Elsevier2022

The Debiased Spatial Whittle likelihood

Sofia Charlotta Olhede

We provide a computationally and statistically efficient method for estimating the parameters of a stochastic covariance model observed on a regular spatial grid in any number of dimensions. Our proposed method, which we call the Debiased Spatial Whittle l ...

WILEY2022

Phantom Curves: Scientific Discovery through Interactive Music Visualization

Fabian Claude Moss, Daniel Harasim

We introduce phantom curves, a novel music-theoretical concept based on the discrete Fourier transform (DFT), and document the creative process that led to their discovery. In particular, we emphasize the importance of interactive web applications for musi ...

ACM2022

Text as signal. A tutorial with case studies focusing on social media (Twitter)

Erick Jorge Canales Rodriguez

Sentiment analysis is the automated coding of emotions expressed in text. Sentiment analysis and other types of analyses focusing on the automatic coding of textual documents are increasingly popular in psychology and computer science. However, the potenti ...

SPRINGER2022

LHC Schottky Spectrum from Macro-Particle Simulations

Tatiana Pieloni, Nicolas Frank Mounet, Christophe Emmanuel R. Lannoy

We introduce a method for building Schottky spectra from macro-particle simulations performed with the PyHEADTAIL code, applied to LHC beam conditions. In this case, the use of a standard Fast Fourier Transform (FFT) algorithm to recover the spectral conte ...

JACoW Publishing2022

On the reconstruction of the attenuation function of a return-stroke current from the Fourier Transform of finite-duration measurements

Farhad Rachidi-Haeri, Marcos Rubinstein

A correct representation of the lightning current is crucial when the electromagnetic field radiated to a point of interest has to be computed. Based on the engineering models of Transmission Line type, such representation involves the knowledge of the ret ...

2022

Leveraging topology, geometry, and symmetries for efficient Machine Learning

Michaël Defferrard

When learning from data, leveraging the symmetries of the domain the data lies on is a principled way to combat the curse of dimensionality: it constrains the set of functions to learn from. It is more data efficient than augmentation and gives a generaliz ...

EPFL2022

Differentiated consistency for worldwide gossips

Pierre-Louis Blaise Roman

Eventual consistency is a consistency model that favors liveness over safety. It is often used in large-scale distributed systems where models ensuring a stronger safety incur performance that are too low to be deemed practical. Eventual consistency tends ...

2022

Natural competence of the pathogen Acinetobacter baumannii: an elusive phenomenon

Nina Vesel

Natural competence for transformation is an important driver of horizontal DNA exchange between different organisms. This can result in accumulation of dangerous genetic features, such as antibiotic resistance genes, in a single organism. One example of an ...

EPFL2022

Localization errors of the stochastic heat equation

David Jean-Michel Candil

In this thesis, we study the stochastic heat equation (SHE) on bounded domains and on the whole Euclidean space

\R^d.

We confirm the intuition that as the bounded domain increases to the whole space, both solutions become arbitrarily close to one another ...

EPFL2022

Generalised Implicit Neural Representations

Pierre Vandergheynst, Daniele Grattarola

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