Výsledky vyhledávání - "M. N. El Korso"

Two-Dimensional Robust Source Localization Under Non-Gaussian Noise

Autor: M. Hamadouche, M. N. El Korso, A. Bouiba, Mohand Lagha, Philippe Forster, Arnaud Breloy

Publikováno v: Circuits, Systems, and Signal Processing. 39:4740-4761

Various methods have been proposed to estimate the direction of arrival (DOA) of sources under the assumption of Gaussian noise. This assumption, based on the central limit theorem, has been mainly used because it offers an appropriate model in a hom

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7d6cda218b0aa1c9bcccaaa3edf3a577
https://doi.org/10.1007/s00034-020-01381-2

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Robust mean and covariance matrix estimation under heterogeneous mixed-effects model with missing values

Autor: M. N. El Korso, Arnaud Breloy, A. Hippert Ferrer, Guillaume Ginolhac

Publikováno v: Signal Processing
Signal Processing, 2021, 188, pp.108195. ⟨10.1016/j.sigpro.2021.108195⟩
Signal Processing, Elsevier, 2021, 188, pp.108195. ⟨10.1016/j.sigpro.2021.108195⟩

International audience; In this paper, robust mean and covariance matrix estimation are considered in the context of mixed-effects models. Such models are widely used to analyze repeated measures data which arise in several signal processing applicat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b0b373a6df01ca690963a4aeb437a70
https://hal.univ-grenoble-alpes.fr/hal-03273077/file/Alex_SP_21.pdf

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On the Recursions of Robust COMET Algorithm for Convexly Structured Shape Matrix

Autor: Bruno Meriaux, Chengfang Ren, P. Forste, Arnaud Breloy, M. N. El Korso, Jean-Philippe Ovarlez

Publikováno v: 27th European Signal Processing Conference (EUSIPCO 2019)
27th European Signal Processing Conference (EUSIPCO 2019), Sep 2019, A Coruña, Spain
HAL
EUSIPCO

International audience; This paper addresses robust estimation of structured shape (normalized covariance) matrices. Shape matrices most often own a particular structure depending on the application of interest and taking this structure into account

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a1518df9541719af0a794434efeaa55
https://hal.archives-ouvertes.fr/hal-02155905/document

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Signal subspace change detection in structured covariance matrices

Autor: Abigael Taylor, R. Ben Abdallah, Arnaud Breloy, M. N. El Korso, D. Lautru

Publikováno v: 27th European Signal Processing Conference
27th European Signal Processing Conference, Sep 2019, Coruna, Spain
EUSIPCO

International audience; Testing common properties between covariance matricesis a relevant approach in a plethora of applications. In thispaper, we derive a new statistical test in the context of structuredcovariance matrices. Specifically, we consid

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6608066ffa632554db92bc8956c848b0

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Bayesian Robust Signal Subspace Estimation in Non-Gaussian Environment

Autor: Arnaud Breloy, M. N. El Korso, R. Ben Abdallah, D. Lautru

Publikováno v: 27th European Signal Processing Conference
27th European Signal Processing Conference, Sep 2019, Coruna, Spain
EUSIPCO

International audience; In this paper, we focus on the problem of low ranksignal subspace estimation. Specifically, we derive new subspaceestimator using the Bayesian minimum mean square distanceformulation. This approach is useful to overcome the is

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0774fdbc4ce10e438ec8cab8d7a4510b
https://hal.parisnanterre.fr/hal-02333872/document

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Bayesian Signal Subspace Estimation with Compound Gaussian Sources

Autor: R. Ben Abdallah, D. Lautru, M. N. El Korso, Arnaud Breloy

Publikováno v: Signal Processing
Signal Processing, Elsevier, 2019, 167, pp.107310. ⟨10.1016/j.sigpro.2019.107310⟩
Signal Processing, 2019, 167, pp.107310. ⟨10.1016/j.sigpro.2019.107310⟩

International audience; In this paper, we consider the problem of low dimensional signal subspace estimation in a Bayesian con- text. We focus on compound Gaussian signals embedded in white Gaussian noise, which is a realistic modeling for various ar

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::032b01773fd395f0f1a52f2e3a99ccce
https://hal.archives-ouvertes.fr/hal-02305119/file/1-s2.0-S0165168419303639-main.pdf

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Méthodes de détection basées sur les matrices de covariance structurée pour le traitement d'images SAR multivariées

Autor: R. Ben Abdallah, Ammar Mian, Abigael Taylor, Arnaud Breloy, M. N. El Korso, D. Lautru

Publikováno v: IEEE Geoscience and Remote Sensing Letters
IEEE Geoscience and Remote Sensing Letters, 2019, 16 (7), pp.1160-1164. ⟨10.1109/LGRS.2018.2890155⟩
IEEE Geoscience and Remote Sensing Letters, IEEE-Institute of Electrical and Electronics Engineers, 2019, 16 (7), pp.1160-1164. ⟨10.1109/LGRS.2018.2890155⟩

International audience; Testing the similarity of covariance matrices from groups of observations has been shown to be a relevant approach for change and/or anomaly detection in synthetic aperture radar images. While the term “similarity” usually

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::793cf908c1a2a15ce7070e8758ffe641
https://hal.science/hal-02305115

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Designing Sar Images Change-point Estimation Strategies Using an Mse Lower Bound

Autor: Jean-Philippe Ovarlez, Lucien Bacharach, M. N. El Korso, Guillaume Ginolhac, Ammar Mian, Alexandre Renaux

Publikováno v: ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, May 2019, Brighton, United Kingdom. pp.5312-5316, ⟨10.1109/ICASSP.2019.8682875⟩
ICASSP

A growing problem in the remote sensing community concerns the estimation of change-points in a time series of Synthetic Aperture Radar (SAR) images. Although the methodologies of change-point estimation have already been investigated in the literatu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::585f0de7ad0aa49ae586a0393dce00e6
https://hal.archives-ouvertes.fr/hal-02152199v2/file/icassp_paper_2019.pdf

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Robust Subspace Clustering for Radar Detection

Autor: M. N. El Korso, Hamid Krim, Ashkan Panahi, Arnaud Breloy

Publikováno v: EUSIPCO

Target detection embedded in a complex interference background such as jamming or strong clutter is an important problem in signal processing. Traditionally, statistical adaptive detection processes are built from a binary hypothesis test performing

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::013ecd0c706c68db6f0c6199a697d7e6
https://doi.org/10.23919/eusipco.2018.8553325

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Bayesian Calibration using Different Prior Distributions: an Iterative Maximum A Posteriori Approach for Radio Interferometers

Autor: Remy Boyer, Pascal Larzabal, M. N. El Korso, André Ferrari, V. Ollier

Publikováno v: 26th European Signal Processing Conference (EUSIPCO 2018)
26th European Signal Processing Conference (EUSIPCO 2018), Sep 2018, Rome, Italy
EUSIPCO

International audience; In this paper, we aim to design robust estimation techniques based on the compound-Gaussian (CG) process and adapted for calibration of radio interferometers. The motivation beyond this is due to the presence of outliers leadi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6fda101ba3a2c18456ac62edd2275168
http://arxiv.org/abs/1807.11382

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