Publications associées (5)

A Local Law for Singular Values from Diophantine Equations

Marius Christopher Lemm

We introduce the N×NN\times N random matrices Xj,k=exp(2πiq=1d ωj,qkq)with {ωj,q}1jN1qd i.i.d. random variables,X_{j,k}=\exp\left(2\pi i \sum_{q=1}^d\ \omega_{j,q} k^q\right) \quad \text{with } \{\omega_{j,q}\}_{\substack{1\leq j\leq N\\ 1\leq q\leq d}} \text{ i.i.d. random variables}, and dd a fixed integer. We pr ...
2020

Locally supported tangential vector, n-vector, and tensor fields

Christopher Brandt

We introduce a construction of subspaces of the spaces of tangential vector, n-vector, and tensor fields on surfaces. The resulting subspaces can be used as the basis of fast approximation algorithms for design and processing problems that involve tangenti ...
WILEY2020

Numerical Solution of the Monodomain Equation: an Inverse Problem for Infarction Models

Emmanuel Augustin Julien Froustey

This project deals with the finite element approximation of an inverse problem for the monodomain equation, which models the propagation of the electrical potential in the cardiac muscle. The goal consists in recovering the shape of an infarcted area inside ...
2012

Sparse Source Recovery from Boundary Measurements using an Extension of Prony's Method for the Poisson Equation

Djano Kandaswamy

Electroencephalography (EEG) is a key modality to monitor brain activity with high temporal resolution. EEG makes use of an array of electrodes to measure the electrical potential on the scalp. While most traditional EEG analyses have looked at EEG rhythms ...
EPFL2011

The "Liquid Computer": A Novel Strategy for Real-Time Computing on Time Series

Henry Markram

We will discuss in this survey article a new framework for analysing computations on time series and in particular on spike trains, introduced in (Maass et. al. 2002). In contrast to common computational models this new framework does not require that info ...
2002

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