Publication

Shortest-support multi-spline bases for generalized sampling

Publications associées (28)

A finite element framework based on bivariate simplex splines on triangle configurations

Recently, triangle configuration based bivariate simplex splines (referred to as TCB-spline) have been introduced to the geometric computing community. TCB-splines retain many attractive theoretic properties of classical B-splines, such as partition of uni ...

ELSEVIER SCIENCE SA2019

The influence of the incommensurately modulated structure on the physical properties of Fe1.35Ge

Helmuth Berger, László Forró, Alla Arakcheeva, Philip Pattison, Krunoslav Prsa, Jacim Jacimovic, Sergiy Katrych, Andrea Pisoni

Single crystal growth by chemical vapour transport has resulted samples with Fe1.35Ge stoichiometry. Structural study has shown that the large number of vacancies introduces an incommensuately modulated structure. The electrical resistivity is in the 200 m ...

2019

Mirrored Langevin Dynamics

Volkan Cevher, Paul Thierry Yves Rolland, Ya-Ping Hsieh, Ali Kavis

We consider the problem of sampling from constrained distributions, which has posed significant challenges to both non-asymptotic analysis and algorithmic design. We propose a unified framework, which is inspired by the classical mirror descent, to derive ...

2018

Robust H-infinity Controller Design Using Frequency-Domain Data via Convex Optimization

Alireza Karimi, Yuanming Zhu, Achille Nicoletti

A new robust controller design method that satisfies the H-infinity criterion is developed for linear time-invariant single-input single-output (SISO) systems. A data-driven approach is implemented in order to avoid the unmodeled dynamics associated with p ...

Wiley-Blackwell2018

Propagating transport-code input parameter uncertainties with deterministic sampling

Patrick Blanchard, Basil Duval, Ambrogio Fasoli, Yves Martin, Richard Pitts, Olivier Sauter, Henri Weisen, Robin Humphry-Baker, Stefano Coda, Martinus Gijs, Partha Dutta, Marco Wischmeier, Jan Horacek, Vlad Trifa, Yann Camenen, Jonathan Graves, Duccio Testa, Miguel Fernández Ruiz, Sun Hee Kim, Mikhail Maslov, Javier García Hernández, David Pfefferlé, José Pedro Rebelo Ferreira Marques, Julio Rodriguez, Pedro Camilo de Oliveira e Silva, Rebecca Hill, Daniel Scott Alessi, Jonnathan Cesar Hidalgo Acosta, Ana Francisca Leal Silva Soares, Dalziel Joseph Wilson, Pierre-Thomas Paul Brun, Jonathan Marc Philippe Faustin, Federico Nespoli, Alberto Hernando de Castro, Hamish William Patten, Bruno Emanuel Ferreira De Sousa Correia, Li Shuai, Nicola Vianello, Antonio José Pereira de Figueiredo, Samuel Lanthaler, Liang Yao, Arnout Lodewijk M Beckers, Cristian Sommariva, Davide Galassi, Alessandro Pau, Yao Zhou, Otto Asunta, Bernhard Sieglin

A novel approach to uncertainty quantification in codes simulating fusion plasma, deterministic sampling (DS), is evaluated. This method uses a few carefully selected samples and can be used to propagate input parameter uncertainties through calculations w ...

2018

A Data-Driven Frequency-Domain Approach for Robust Controller Design via Convex Optimization

Achille Nicoletti

The objective of this dissertation is to develop data-driven frequency-domain methods for designing robust controllers through the use of convex optimization algorithms. Many of today's industrial processes are becoming more complex, and modeling accurate ...

EPFL2018

Sampling at unknown locations: Uniqueness and reconstruction under constraints

Martin Vetterli, Golnooshsadat Elhami, Benjamin Bejar Haro, Adam James Scholefield, Michalina Wanda Pacholska

Traditional sampling results assume that the sample locations are known. Motivated by simultaneous localization and mapping (SLAM) and structure from motion (SfM), we investigate sampling at unknown locations. Without further constraints, the problem is of ...

2018

Periodic Splines and Gaussian Processes for the Resolution of Linear Inverse Problems

Michaël Unser, Julien René Pierre Fageot, Anaïs Laure Marie-Thérèse Badoual

This paper deals with the resolution of inverse problems in a periodic setting or, in other terms, the reconstruction of periodic continuous-domain signals from their noisy measurements. We focus on two reconstruction paradigms: variational and statistical ...

2018