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Concept

Algorithme d'Euclide étendu

Publications associées (9)

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

SVR-AMA: An Asynchronous Alternating Minimization Algorithm With Variance Reduction for Model Predictive Control Applications

Colin Neil Jones, Ye Pu

This paper focuses on the design of an asynchronous dual solver suitable for model predictive control (MPC) applications. The proposed solver relies on a state-of-the-art variance reduction (VR) scheme, previously used in the context of proximal stochastic ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Symplectic Model-Reduction with a Weighted Inner Product

Jan Sickmann Hesthaven, Babak Maboudi Afkham

In the recent years, considerable attention has been paid to preserving structures and invariants in reduced basis methods, in order to enhance the stability and robustness of the reduced system. In the context of Hamiltonian systems, symplectic model redu ...

2018

Efficient Multi-dimensional Diracs Estimation with Linear Sample Complexity

Martin Vetterli, Thierry Blu, Hanjie Pan

Estimating Diracs in continuous two or higher dimensions is a fundamental problem in imaging. Previous approaches extended one dimensional methods, like the ones based on finite rate of innovation (FRI) sampling, in a separable manner, e.g., along the hori ...

2018

On finitely generated modules over quasi-Euclidean rings

Luc Guyot

Let R be a unital commutative ring, and let M be an R-module that is generated by k elements but not less. Let be the subgroup of generated by the elementary matrices. In this paper we study the action of by matrix multiplication on the set of unimodular r ...

Springer Verlag2017

Sensitive and Accurate Dispersion Map Extraction of HNLFs by Frequency Tuning of a Degenerate FWM

Camille Sophie Brès, Fatemeh Alishahi, Armand Vedadi-Comte, Mohammad Amin Shoaie

A sensitive and accurate method for dispersion map extraction along an arbitrarily profiled highly nonlinear fiber (HNLF) is proposed. High sensitivity is achieved by positioning the wavelength of a signal at the band edge of the modulation instability (MI ...

IEEE Institute of Electrical and Electronics Engineers2016

Constrained expectation-maximization algorithm for stochastic inertial error modeling: study of feasibility

Jan Skaloud, Stéphane Guerrier, Yannick Stebler

Stochastic modeling is a challenging task for low-cost sensors whose errors can have complex spectral structures. This makes the tuning process of the INS/GNSS Kalman filter often sensitive and difficult. For example, first-order Gauss–Markov processes are ...

IOP Publishing2011

High-Performance Modular Multiplication on the Cell Processor

Joppe Willem Bos

This paper presents software implementation speed records for modular multiplication arithmetic on the synergistic processing elements of the Cell broadband engine (Cell) architecture. The focus is on moduli which are of special interest in elliptic curve ...

Springer2010

Automatic Verification of Parametric Specifications with Complex Topologies

Swen Jacobs

The focus of this paper is on reducing the complexity in verification by exploiting modularity at various levels: in specification, in verification, and structurally. For specifications, we use the modular language CSP-OZ-DC, which allows us to decouple ve ...

2010