Frédéric Pascal
22
Documents
Identifiants chercheurs
- frederic-pascal
- 0000-0003-0196-6395
- Google Scholar : https://scholar.google.fr/citations?user=sGpusG8AAAAJ
- IdRef : 111704898
Présentation
**Frederic Pascal** received the Master's degree ("Probabilities, Statistics and Applications: Signal, Image et Networks";) with merit, in Applied Statistics from University Paris VII - Jussieu, Paris, France, in 2003. Then, he received the **Ph.D. degree** of Signal Processing, from University Paris X - Nanterre in 2006. From November 2006 to February 2008, he made a post-doctoral position in the Signal Processing and Information team of the laboratory SATIE, CNRS, ENS Cachan, France. Between March 2008 and December 2011 (resp. Jan. 2012 - Dec. 2013), he was an Assistant Professor (resp. Associate Professor) in SONDRA at CentraleSupelec. In 2012, he obtained a **Research Directorship Habilitation** (HDR) thesis in Signal Processing from the University of Paris-Sud. Between Aug. 2013 and Aug. 2014, he was a Visiting Associate Professor in the ECE department at the National University of Singapore. From Jan. 2014, Frederic Pascal is a full Professor in the L2S laboratory at CentraleSupelec. From Jan. 2017 to Dec. 2019, he was the head of the "Signals and Statistics"; group of L2S. He is also the **coordinator of Artificial Intelligence and Data Science activities at CentraleSupelec**. From 2015 to 2017, Frederic Pascal was the Chair of the EURASIP SAT in Theoretical and Methodological Trends in Signal Processing (TMTSP) and he is a member of the IEEE SPS SAM technical committee (Jan. 2015-present). Frederic Pascal serves as an Associate Editor for the IEEE TSP (2015-2018), Elsevier SP (2018-present) and EURASIP JASP (2015-present). His research interests contain **estimation, detection and classification for statistical signal processing and applications**. He is the author / coauthor of more than one hundred papers in the top journals and conferences in **Signal Processing, Image Processing and Statistics / Machine Learning**.
More details at:
Web: <http://www.fredericpascal.blogspot.com>
LinkedIn: [https://www.linkedin.com/in/frederic-pascal-937a3030/](https://www.linkedin.com/in/frederic-pascal-937a3030/ "https://www.linkedin.com/in/frederic-pascal-937a3030/")
Google Scholar: [https://scholar.google.fr/FP](https://www.linkedin.com/in/frederic-pascal-937a3030/ "https://scholar.google.fr/citations?hl=en&user=sGpusG8AAAAJ&view_op=list_works&gmla=AJsN-F4r7aXr3MfqUH84f-imm19vWpGuHIvqUjrNIl7hGc14koVS2Ke3c6Fk0bCcncSeyYR_SRPT8CtOsDM_iNt3N5B2HEas8ch2qyL1Vm3_lwLfsLFj9YXqyPvZ0ONXeLAajs577LMsFn1PbpEMfPY5ZPWMhFhwdMjJe9AXl8RzRPi44QyDX6Kv5iL8JLZTL7KwT6K-dDP0")
Publications
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Riemannian framework for robust covariance matrix estimation in spiked modelsICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2020, Barcelona, Spain. ⟨10.1109/icassp40776.2020.9054726⟩
Communication dans un congrès
hal-02571084v1
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Spectral Shrinkage of Tyler's M -Estimator of Covariance Matrix8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2019), Dec 2019, Guadeloupe, West Indies, France. ⟨10.1109/camsap45676.2019.9022652⟩
Communication dans un congrès
hal-02485823v1
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Caractérisations asymptotiques pour les composantes principales des M -estimateursGRETSI 2019 - XXVIIème Colloque francophone de traitement du signal et des images, Aug 2019, Lille, France
Communication dans un congrès
hal-02486933v1
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New asymptotic properties for the robust ANMFThe 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017), Mar 2017, New Orleans, United States. ⟨10.1109/ICASSP.2017.7952793⟩
Communication dans un congrès
hal-01816123v1
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Nouvelles propriétés asymptotiques de détecteurs robustesVingt-sixième Colloque GRETSI 2017, Sep 2017, Juan-les-Pins, France
Communication dans un congrès
hal-02486099v1
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A robust signal subspace estimator2016 IEEE Statistical Signal Processing Workshop (SSP), Jun 2016, Palma de Majorque, Spain. ⟨10.1109/ssp.2016.7551737⟩
Communication dans un congrès
hal-01323380v1
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Estimation Robuste de la Matrice de Covariance en contexte Hétérogène Rang Faible25eme Colloque francophone de traitement du signal et des images (GRETSI 2015), Sep 2015, Lyon, France. pp.1-4
Communication dans un congrès
hal-01226415v1
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Asymptotic Detection Performance Analysis of the Robust Adaptive Normalized Matched FilterIEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2015), Dec 2015, Cancun, Mexico. ⟨10.1109/CAMSAP.2015.7383755⟩
Communication dans un congrès
hal-01325083v1
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Numerical performances of low rank stap based on different heterogeneous clutter subspace estimators2014 International Radar Conference , Oct 2014, Lille, France. ⟨10.1109/RADAR.2014.7060426⟩
Communication dans un congrès
hal-01084418v1
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Robust estimation of the clutter subspace for a Low Rank heterogeneous noise under high Clutter to Noise Ratio assumption2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), May 2014, Florence, Italy. pp.1-5, ⟨10.1109/ICASSP.2014.6853559⟩
Communication dans un congrès
hal-01024200v1
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CFAR property and robustness of the lowrank adaptive normalized matched filters detectors in low rank compound gaussian context2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM 2014) , Jun 2014, La Corogne, Spain. pp.301 - 304, ⟨10.1109/SAM.2014.6882401⟩
Communication dans un congrès
hal-01059726v1
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Estimation par Maximum de Vraisemblance du sous espace clutter dans un bruit hétérogène rang faible avec application au STAPGRETSI 2013, Sep 2013, Brest, France. pp.1-4
Communication dans un congrès
hal-00871207v1
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MAXIMUM LIKELIHOOD ESTIMATION OF CLUTTER SUBSPACE IN NON HOMOGENEOUS NOISE CONTEXT21st European Signal Processing Conference (EUSIPCO 2013), Sep 2013, Marrakech, Morocco. pp.1-5
Communication dans un congrès
hal-00871219v1
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Détection de changements basée sur les covariances de séries d’images SARISTE Edition. Détection de changements et analyse des séries temporelles d’images 1: Méthodes non supervisées, 2022
Chapitre d'ouvrage
hal-04014783v1
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An Overview of Covariance‐based Change Detection Methodologies in Multivariate SAR Image Time SeriesChange Detection and Image Time Series Analysis 1, 1, Wiley, 2021, ⟨10.1002/9781119882268.ch3⟩
Chapitre d'ouvrage
hal-03519630v1
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