Concept

Bayes estimator

Publications associées (440)

Host shift and cospeciation rate estimation from co-phylogenies

Host shifts can cause novel infectious diseases, and is a key process in diversification. Disentangling the effects of host shift vs. those of cospeciation is non-trivial as both can result in phylogenic congruence. We develop a new framework based on netw ...

Wiley2017

EchoSLAM: Simultaneous Localization and Mapping with Acoustic Echoes

Martin Vetterli, Ivan Dokmanic, Miranda Krekovic

We address the problem of jointly localizing a robot in an unknown room and estimating the room geometry from echoes. Unlike earlier work using echoes, we assume a completely autonomous setup with (near) collocated microphone and the acoustic source. We fi ...

Ieee2016

Robust 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 Ag2016

Adaptive Assistance for Brain-Computer Interfaces by Online Prediction of Command Reliability

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Robert Leeb, Sareh Saeedi

One of the challenges of using brain-computer interfaces (BCIs) over extended periods of time is the variation of the users' performance across different experimental days. The goal of the current study is to propose a performance estimator for an electroe ...

Institute of Electrical and Electronics Engineers2016

Design of a Distributed Quantized Luenberger Filter for Bounded Noise

Colin Neil Jones, Ye Pu, Andrea Alessandretti, Francisco Fernandes Castro Rego

This paper addresses the problem of distributed state estimation for linear systems with process and measurement noise, in the case of limited communication data rate, where the data exchanged between agents is quantized. We propose a linear distributed Lu ...

Ieee2016

A posteriori error estimation for partial differential equations with random input data

Diane Sylvie Guignard

This thesis is devoted to the derivation of error estimates for partial differential equations with random input data, with a focus on a posteriori error estimates which are the basis for adaptive strategies. Such procedures aim at obtaining an approximati ...

EPFL2016

Performance Assessment of Linear State Estimators Using Synchrophasor Measurements

Jean-Yves Le Boudec, Mario Paolone, Lorenzo Zanni, Styliani Sarri, Miroslav Popovic

This paper aims to assess the performance of linear state estimation (SE) processes of power systems relying on synchrophasor measurements. The performance assessment is conducted with respect to two different families of SE algorithms, i.e., static ones r ...

Institute of Electrical and Electronics Engineers2016

A posteriori error estimations for elliptic partial differential equations with small uncertainties

Fabio Nobile, Marco Picasso, Diane Sylvie Guignard

In this article, a finite element error analysis is performed on a class of linear and nonlinear elliptic problems with small uncertain input. Using a perturbation approach, the exact (random) solution is expanded up to a certain order with respect to a pa ...

2016

Diffusion Adaptation over Multi-Agent Networks with Wireless Link Impairments

Ali H. Sayed

We study the performance of diffusion least-mean squares algorithms for distributed parameter estimation in multi-agent networks when nodes exchange information over wireless communication links. Wireless channel impairments, such as fading and path-loss, ...

IEEE2016

A new method to break the mass-sheet degeneracy using aperture moments

Jean-Paul Richard Kneib, Markus Rexroth

Mass determinations from gravitational lensing shear and the higher order estimator flexion are both subject to the mass-sheet degeneracy. Mass sheet degeneracy refers to a transformation that leaves the reduced shear and flexion invariant. In general, thi ...

Oxford Univ Press2016

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