Publications associées à A new method for solving broadband matching problems

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Approximation of Quantities of Interest in Stochastic PDEs by the Random Discrete $L^2$ Projection on Polynomial Spaces

Fabio Nobile, Giovanni Migliorati, Erik Gustaf Bogislaw Von Schwerin

In this work we consider the random discrete

L^2

projection on polynomial spaces (hereafter RDP) for the approximation of scalar quantities of interest (QOIs) related to the solution of a partial differential equation model with random input parameters. ...

Siam Publications2013

A new method for solving broadband matching problems

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MATHICSE Technical Report : A Multilevel Stochastic Gradient method for PDE-constrained Optimal Control Problems with uncertain parameters

Frequency domain theory for functional time series: Variance decomposition and an invariance principle

Scalable Learning-Based Sampling Optimization for Compressive Dynamic MRI

A new analysis approach for T-2 relaxometry myelin water quantification: Orthogonal Matching Pursuit

Medium Frequency Transformer Leakage Inductance Modeling and Experimental Verification

The recursive Hessian sketch for adaptive filtering

Adaptive polynomial approximation by means of random discrete least squares

Analysis of resonant planar dissipative network antennas for rf inductively coupled plasma sources

Resonant RF network antennas for large-area and large-volume inductively coupled plasma sources

Approximation of Quantities of Interest in Stochastic PDEs by the Random Discrete $L^2$ Projection on Polynomial Spaces

Approximation of Quantities of Interest in Stochastic PDEs by the Random Discrete $L^2$ Projection on Polynomial Spaces

Resonant RF network antennas for large-area and large-volume inductively coupled plasma sources

Analysis of resonant planar dissipative network antennas for rf inductively coupled plasma sources

Adaptive polynomial approximation by means of random discrete least squares

The recursive Hessian sketch for adaptive filtering

Medium Frequency Transformer Leakage Inductance Modeling and Experimental Verification

A new analysis approach for T-2 relaxometry myelin water quantification: Orthogonal Matching Pursuit

Scalable Learning-Based Sampling Optimization for Compressive Dynamic MRI

Frequency domain theory for functional time series: Variance decomposition and an invariance principle

MATHICSE Technical Report : A Multilevel Stochastic Gradient method for PDE-constrained Optimal Control Problems with uncertain parameters