Concept
Extremum estimator
Related publications (41)
Jump-Penalized Least Absolute Values Estimation of Scalar or Circle-Valued Signals
Michaël Unser, Martin Kurt Storath
We study jump-penalized estimators based on least absolute deviations which are often referred to as Potts estimators. They are estimators for a parsimonious piecewise constant representation of noisy data having a noise distribution which has heavier tail ...
Oxford University Press2017Research online: Robust tightly coupled GNSS/INS estimation for navigation
Jan Skaloud, Omar Garcia Crespillo, Michael Meurer
We designed a tightly-coupled integration between GNSS and inertial navigation systems (INS) where we modify the update step of a classical Extended Kalman Filter (EKF) to consider different robust estimators (such as M-estimators). We consider different f ...
2017Robust Tightly Coupled GNSS/INS Estimation for Navigation in Challenging Scenarios
Jan Skaloud, Omar Garcia Crespillo, Michael Meurer
The combination of Global Navigation Satellite Systems (GNSS) and Inertial Navigation System (INS) has become the baseline of many transportation applications. In this work, we design a tightly-coupled integration between GNSS and INS where we modify the u ...
2017Blowing in the Wind
Every day tons of pollutants are emitted into the atmosphere all around the world. These pollutants are altering the equilibrium of our planet, causing profound changes in its climate, increasing global temperatures, and raising the sea level. The need to ...
EPFL2017Robust compressive sensing of sparse signals: A review
Alonso Ramirez Manzanares, Rafael Eduardo Carrillo Rangel
Compressive sensing generally relies on the L2-norm for data fidelity, whereas in many applications robust estimators are needed. Among the scenarios in which robust performance is required, applications where the sampling process is performed in the prese ...
Springer International Publishing Ag2016Likelihood estimators for multivariate extremes
Anthony Christopher Davison, Raphaël Huser
The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high t ...
Springer2016Beyond Allan Variance - GMWM Framework For Sensor Calibration
Jan Skaloud, Stéphane Guerrier
Proposed 50 years ago for studying stability of oscillators, Allan Variance (AV) was accepted by IEEE as a standard for characterizing behavior of sensors. However, the inverse mapping, i.e. the estimation of noise-parameters from Allan Variance is less st ...
2015Reference-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 Engineers2014Direct path integral estimators for isotope fractionation ratios
Michele Ceriotti, Bingqing Cheng
Fractionation of isotopes among distinct molecules or phases is a quantum effect which is often exploited to obtain insights on reaction mechanisms, biochemical, geochemical, and atmospheric phenomena. Accurate evaluation of isotope ratios in atomistic sim ...
American Institute of Physics2014Statistical Inference for Partially Observed Stochastic Epidemics
This work is concerned with the estimation of the spreading potential of the disease in the initial stages of an epidemic. A speedy and accurate estimation is important for determining whether or not interventions are necessary to prevent a major outbreak. ...
EPFL2013