Publications associées à M-estimateur

A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

Martin Vetterli, Ali Zoubir, Marta Martinez-Camara

Solving a linear inverse problem may include difficulties such as the presence of outliers and a mixing matrix with a large condition number. In such cases a regularized robust estimator is needed. We propose a new tau-type regularized robust estimator tha ...

2015

Exploiting task constraints for self-calibrated brain-machine interface control using error-related potentials

Inaki Asier Iturrate Gil

This paper presents a new approach for self-calibration BCI for reaching tasks using error-related potentials. The proposed method exploits task constraints to simultaneously calibrate the decoder and control the device, by using a robust likelihood functi ...

Public Library of Science2015

Guided Mesh Normal Filtering

Sofien Bouaziz, Bailin Deng

The joint bilateral filter is a variant of the standard bilateral filter, where the range kernel is evaluated using a guidance signal instead of the original signal. It has been successfully applied to various image processing problems, where it provides m ...

Wiley-Blackwell2015

An overview of robust compressive sensing of sparse signals in impulsive noise

Alonso Ramirez Manzanares, Rafael Eduardo Carrillo Rangel

While compressive sensing (CS) has traditionally relied on L2 as an error norm, a broad spectrum of applications has emerged where robust estimators are required. Among those, applications where the sampling process is performed in the presence of impulsiv ...

2015

Likelihood Estimation for the INAR(p) Model by Saddlepoint Approximation

Anthony Christopher Davison

Saddlepoint techniques have been used successfully in many applications, owing to the high accuracy with which they can approximate intractable densities and tail probabilities. This article concerns their use for the estimation of high-order integer-value ...

American Statistical Association2015

Fast and Accurate Inference of Plackett-Luce Models

Matthias Grossglauser, Lucas Maystre

We show that the maximum-likelihood (ML) estimate of models derived from Luce’s choice axiom (e.g., the Plackett–Luce model) can be expressed as the stationary distribution of a Markov chain. This conveys insight into several recently proposed spectral inf ...

2015

Reference-Free Automated Magnetic Sensor Calibration for Angle Estimation in Smart Knee Prostheses

Kamiar Aminian, Julien David Rechenmann, Arash Arami

In this work, we present a method for automated calibration of an implanted anisotropic magnetoresistive (AMR) sensor for measuring the internal-external rotation (IE) in a prosthetic knee without using any reference measurement. The measurement system con ...

Institute of Electrical and Electronics Engineers2014

Adaptive Image Resizing Based on Continuous-Domain Stochastic Modeling

Michaël Unser, John Paul Ward, Aurélien Bourquard, Hagay Kirshner

We introduce an adaptive continuous-domain modeling approach to texture and natural images. The continuous-domain image is assumed to be a smooth function, and we embed it in a parameterized Sobolev space. We point out a link between Sobolev spaces and sto ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Outlier removal for improved source estimation in atmospheric inverse problems

Martin Vetterli, Marta Martinez-Camara

Estimation of the quantities of harmful substances emitted into the atmosphere is one of the main challenges in modern environmen- tal sciences. In most of the cases, this estimation requires solving a linear inverse problem. A key difficulty in evaluating ...

Ieee2014

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M-estimateur

A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

Beyond Allan Variance - GMWM Framework For Sensor Calibration

Exploiting task constraints for self-calibrated brain-machine interface control using error-related potentials

Guided Mesh Normal Filtering

An overview of robust compressive sensing of sparse signals in impulsive noise

Likelihood Estimation for the INAR(p) Model by Saddlepoint Approximation

Fast and Accurate Inference of Plackett-Luce Models

Reference-Free Automated Magnetic Sensor Calibration for Angle Estimation in Smart Knee Prostheses

Adaptive Image Resizing Based on Continuous-Domain Stochastic Modeling

Outlier removal for improved source estimation in atmospheric inverse problems

Graph Chatbot

Chattez avec Graph Search

Likelihood Estimation for the INAR(p) Model by Saddlepoint Approximation

Guided Mesh Normal Filtering

Exploiting task constraints for self-calibrated brain-machine interface control using error-related potentials

Adaptive Image Resizing Based on Continuous-Domain Stochastic Modeling

Reference-Free Automated Magnetic Sensor Calibration for Angle Estimation in Smart Knee Prostheses

Outlier removal for improved source estimation in atmospheric inverse problems

A new robust and efficient estimator for ill-conditioned linear inverse problems with outliers

Beyond Allan Variance - GMWM Framework For Sensor Calibration

Fast and Accurate Inference of Plackett-Luce Models

An overview of robust compressive sensing of sparse signals in impulsive noise