29 citations · 47 across the 10 of their papers we have counts for
13 papers
Robust Covariance Estimation for Entry-wise Contaminated and Partially Observed Data via Expectation Maximization Algorithm
Matys Savidan, Mohammed Nabil El Korso
Robust covariance estimation under entry-wise contamination and missing data is challenging in various signal processing applications. Under the Student- model, observation-leve…
Dimensionality Reduction for Hyperspectral Image Classification
Mohamed Cherifi, Ammar Mesloub, Mohammed Nabil El Korso +2
This paper addresses the issue of supervised classification in the context of hyperspectral satellite images. It deals with two fundamental aspects: dimensionality reduction of dat…
Robust Expectation-Maximization for Covariance Estimation in SIRV Models with Missing Data: Application to InSAR Time Series
M. Cherifi, M. N. El Korso, A. Hippert-Ferrer +1
This paper presents a robust Expectation-Maximization framework for covariance estimation in Scale-Invariant Random Vector (SIRV) models with missing data under ignorable missingne…
Multifrequency Array Calibration in Presence of Radio Frequency Interferences
Yassine Mhiri, Mohammed Nabil El Korso, Arnaud Breloy +1
Radio interferometers are phased arrays producing high-resolution images from the covariance matrix of measurements. Calibration of such instruments is necessary and is a critical…
Robust low-rank covariance matrix estimation with a general pattern of missing values
Alexandre Hippert-Ferrer, Mohammed Nabil El Korso, Arnaud Breloy +1
This paper tackles the problem of robust covariance matrix estimation when the data is incomplete. Classical statistical estimation methodologies are usually built upon the Gaussia…
Robust Calibration of Radio Interferometers in Non-Gaussian Environment
Virginie Ollier, Mohammed Nabil El Korso, Rémy Boyer +2
The development of new phased array systems in radio astronomy, as the low frequency array (LOFAR) and the square kilometre array (SKA), formed of a large number of small and flexi…
A Bayesian Lower Bound for Parameter Estimation of Poisson Data Including Multiple Changes (extended)
Lucien Bacharach, Mohammed Nabil El Korso, Alexandre Renaux +1
This paper derives lower bounds for the mean square errors of parameter estimators in the case of Poisson distributed data subjected to multiple abrupt changes. Since both change l…
A class of Weiss-Weinstein bounds and its relationship with the Bobrovsky-Mayer-Wolf-Zakai bounds
Eric Chaumette, Alexandre Renaux, Mohammed Nabil El Korso
A fairly general class of Bayesian "large-error" lower bounds of the Weiss-Weinstein family, essentially free from regularity conditions on the probability density functions suppor…
Parallel Calibration for Sensor Array Radio Interferometers
Martin Brossard, Mohammed Nabil El Korso, Marius Pesavento +3
In order to meet the theoretically achievable imaging performance, calibration of modern radio interferometers is a mandatory challenge, especially at low frequencies. In this pers…
Bayesian Lower Bounds for Dense or Sparse (Outlier) Noise in the RMT Framework
Virginie Ollier, Rémy Boyer, Mohammed Nabil El Korso +1
Robust estimation is an important and timely research subject. In this paper, we investigate performance lower bounds on the mean-square-error (MSE) of any estimator for the Bayesi…
Relaxed concentrated MLE for robust calibration of radio interferometers
Virginie Ollier, Mohammed Nabil El Korso, Rémy Boyer +2
In this paper, we investigate the calibration of radio interferometers in which Jones matrices are considered to model the interaction between the incident electromagnetic field an…
Joint ML calibration and DOA estimation with separated arrays
Virginie Ollier, Mohammed Nabil El Korso, Rémy Boyer +2
This paper investigates parametric direction-of-arrival (DOA) estimation in a particular context: i) each sensor is characterized by an unknown complex gain and ii) the array consi…
Coexistence of Near-Field and Far-Field Sources: the Angular Resolution Limit
Rémy Boyer, Mohammed Nabil El Korso, Alexandre Renaux +1
Passive source localization is a well known inverse problem in which we convert the observed measurements into information about the direction of arrivals. In this paper we focus o…