6 papers
Joint Estimation of Location and Scatter in Complex Elliptical Distributions: A robust semiparametric and computationally efficient -estimator of the shape matrix
Stefano Fortunati, Alexandre Renaux, Frédéric Pascal
The joint estimation of the location vector and the shape matrix of a set of independent and identically Complex Elliptically Symmetric (CES) distributed observations is investigat…
Robust Semiparametric DOA Estimation in non-Gaussian Environment
Stefano Fortunati, Alexandre Renaux, Frédéric Pascal
A general non-Gaussian semiparametric model is adopted to characterize the measurement vectors, i.e.\ the \textit{snapshots}, collected by a linear array. Moreover, the recently de…
Properties of a new -estimator of shape matrices
Stefano Fortunati, Alexandre Renaux, Frédéric Pascal
This paper aims at presenting a simulative analysis of the main properties of a new -estimator of shape matrices in Complex Elliptically Symmetric (CES) distributed observations…
Robust Semiparametric Efficient Estimators in Elliptical Distributions
Stefano Fortunati, Alexandre Renaux, Frédéric Pascal
Covariance matrices play a major role in statistics, signal processing and machine learning applications. This paper focuses on the \textit{semiparametric} covariance/scatter matri…
A Riemannian Framework for Low-Rank Structured Elliptical Models
Florent Bouchard, Arnaud Breloy, Guillaume Ginolhac +2
This paper proposes an original Riemmanian geometry for low-rank structured elliptical models, i.e., when samples are elliptically distributed with a covariance matrix that has a l…
Some results on the Weiss-Weinstein bound for conditional and unconditional signal models in array processing
Dinh Thang Vu, Alexandre Renaux, Remy Boyer +1
In this paper, the Weiss-Weinstein bound is analyzed in the context of sources localization with a planar array of sensors. Both conditional and unconditional source signal models…