Département signal et communications

Le département Signal & Communications est spécialisé dans le domaine des Mathématiques et Traitement de l’Information. Il s’intéresse à la fois aux aspects méthodologiques et théoriques mais également aux problèmes de mise en œuvre et des implémentations des algorithmes étudiés notamment via les techniques de radio logicielle. Les domaines d’applications concernent principalement la Mer, la Défense et les Télécommunications.

Le département Signal & Communications est composé en 2018 de quelques 54 membres dont 17 permanents.

Département signal et communications

 

 

Recherche
Enseignement
Innovation
International

Les prochains événements du département

Il n'y a pas d'événement en cours ou à venir pour le département.
Les dernières publications du département
Article dans une revue
Messai Malek, Aissa El Bey Abdeldjalil, Amis Cavalec Karine, Guilloud Frédéric
Iteratively Reweighted two-Stage LASSO for Block-Sparse Signal Recovery Under Finite-Alphabet Constraints
Signal Processing, Elsevier, 2019, 157, pp.73-77. 〈10.1016/j.sigpro.2018.11.007〉
Bibtext :
@article{messai:hal-01933349,
TITLE = {{Iteratively Reweighted two-Stage LASSO for Block-Sparse Signal Recovery Under Finite-Alphabet Constraints}},
AUTHOR = {Messai, Malek and Aissa El Bey, Abdeldjalil and Amis Cavalec, Karine and Guilloud, Fr{\'e}d{\'e}ric},
URL = {https://hal.archives-ouvertes.fr/hal-01933349},
JOURNAL = {{Signal Processing}},
HAL_LOCAL_REFERENCE = {19289},
PUBLISHER = {{Elsevier}},
VOLUME = {157},
PAGES = {73-77},
YEAR = {2019},
MONTH = Apr,
DOI = {10.1016/j.sigpro.2018.11.007},
KEYWORDS = {l1-minimization ; Block-sparsity recovery ; Finite-alphabet ; LASSO ; Iterative recovery algorithms ; Iterative reweighting},
PDF = {https://hal.archives-ouvertes.fr/hal-01933349/file/letter_singlecolumn_final.pdf},
HAL_ID = {hal-01933349},
HAL_VERSION = {v1},
}
Endnote :
%0 Journal Article
%T Iteratively Reweighted two-Stage LASSO for Block-Sparse Signal Recovery Under Finite-Alphabet Constraints
%+ Département Signal et Communications (SC)
%+ Lab-STICC_IMTA_CACS_COM
%A Messai, Malek
%A Aissa El Bey, Abdeldjalil
%A Amis Cavalec, Karine
%A Guilloud, Frédéric
%< avec comité de lecture
%Z 19289
%@ 0165-1684
%J Signal Processing
%I Elsevier
%V 157
%P 73-77
%8 2019-04
%D 2019
%R 10.1016/j.sigpro.2018.11.007
%K l1-minimization
%K Block-sparsity recovery
%K Finite-alphabet
%K LASSO
%K Iterative recovery algorithms
%K Iterative reweighting
%Z Engineering Sciences [physics]/Signal and Image processingJournal articles
%X In this paper, we derive an efficient iterative algorithm for the recovery of block-sparse signals given the finite data alphabet and the non-zero block probability. The non-zero block number is supposed to be far smaller than the total block number (block-sparse). The key principle is the separation of the unknown signal vector into an unknown support vector s and an unknown data symbol vector a. Both number (‖s‖0) and positions (s ∈ {0, 1}) of non-zero blocks are unknown. The proposed algorithms use an iterative two-stage LASSO procedure consisting in optimizing the recovery problem alternatively with respect to a and with respect to s. The first algorithm resorts on ℓ1-norm of the support vector and the second one applies reweighted ℓ1-norm, which further improves the recovery performance. Performance of proposed algorithms is illustrated in the context of sporadic multiuser communications. Simulations show that the reweighted-ℓ1 algorithm performs close to its lower bound (perfect knowledge of the support vector).
%G English
%2 https://hal.archives-ouvertes.fr/hal-01933349/document
%2 https://hal.archives-ouvertes.fr/hal-01933349/file/letter_singlecolumn_final.pdf
%L hal-01933349
%U https://hal.archives-ouvertes.fr/hal-01933349
%~ UNIV-BREST
%~ LAB-STICC_IMTA
%~ IMTA_SC
%~ LAB-STICC_IMTA_CACS_COM
%~ LAB-STICC
%~ ENIB
%~ UNIV-UBS
%~ CNRS
%~ INSTITUT-TELECOM
%~ IMT-ATLANTIQUE
Article dans une revue
Hehdly K., Laaraiedh M., Abdelkefi F., Siala M.
Cooperative localization and tracking in wireless sensor networks
International Journal of Communication Systems, Wiley, 2019, 32 (1)
Bibtext :
@article{hehdly:hal-01973665,
TITLE = {{Cooperative localization and tracking in wireless sensor networks}},
AUTHOR = {Hehdly, K. and Laaraiedh, M. and Abdelkefi, F. and Siala, M. },
URL = {https://hal-imt-atlantique.archives-ouvertes.fr/hal-01973665},
JOURNAL = {{International Journal of Communication Systems, Wiley}},
VOLUME = {32},
NUMBER = {1},
YEAR = {2019},
MONTH = Jan,
HAL_ID = {hal-01973665},
HAL_VERSION = {v1},
}
Endnote :
%0 Journal Article
%T Cooperative localization and tracking in wireless sensor networks
%+ Unité de Recherche en Réseaux Radio Mobile Multimédia (MEDIATRON)
%+ Département Signal et Communications (SC)
%+ Lab-STICC_IMTA_CACS_COM
%A Hehdly, K.
%A Laaraiedh, M.
%A Abdelkefi, F.
%A Siala, M.
%< avec comité de lecture
%J International Journal of Communication Systems, Wiley
%V 32
%N 1
%8 2019-01-10
%D 2019
%Z Engineering Sciences [physics]/Signal and Image processing
%Z Computer Science [cs]/Networking and Internet Architecture [cs.NI]Journal articles
%G English
%L hal-01973665
%U https://hal-imt-atlantique.archives-ouvertes.fr/hal-01973665
%~ IMT-ATLANTIQUE
%~ IMTA_SC
%~ CNRS
%~ UNIV-BREST
%~ UNIV-UBS
%~ INSTITUT-TELECOM
%~ ENIB
%~ LAB-STICC
%~ LAB-STICC_IMTA
%~ LAB-STICC_IMTA_CACS_COM
Communication dans un congrès
Pham Chi-Hieu, Tor-Díez Carlos, Meunier Hélène, Bednarek Nathalie, Fablet Ronan, Passat Nicolas, Rousseau François
Simultaneous super-resolution and segmentation using a generative adversarial network: Application to neonatal brain MRI
International Symposium on Biomedical Imaging (ISBI), 2019, Venice, Italy
Bibtext :
@inproceedings{pham:hal-01895163,
TITLE = {{Simultaneous super-resolution and segmentation using a generative adversarial network: Application to neonatal brain MRI}},
AUTHOR = {Pham, Chi-Hieu and Tor-D{\'i}ez, Carlos and Meunier, H{\'e}l{\`e}ne and Bednarek, Nathalie and FABLET, Ronan and Passat, Nicolas and Rousseau, Fran{\c c}ois},
URL = {https://hal.archives-ouvertes.fr/hal-01895163},
BOOKTITLE = {{International Symposium on Biomedical Imaging (ISBI)}},
ADDRESS = {Venice, Italy},
YEAR = {2019},
KEYWORDS = {segmentation ; super-resolution ; neonatal brain MRI ; 3D generative adversarial networks},
HAL_ID = {hal-01895163},
HAL_VERSION = {v1},
}
Endnote :
%0 Conference Proceedings
%T Simultaneous super-resolution and segmentation using a generative adversarial network: Application to neonatal brain MRI
%+ Laboratoire de Traitement de l'Information Medicale (LaTIM)
%+ Département lmage et Traitement Information (ITI)
%+ Service de médecine néonatale et réanimation pédiatrique, CHU de Reims
%+ Centre de Recherche en Sciences et Technologies de l'Information et de la Communication - EA 3804 (CRESTIC)
%+ Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC)
%+ Département Signal et Communications (SC)
%A Pham, Chi-Hieu
%A Tor-Díez, Carlos
%A Meunier, Hélène
%A Bednarek, Nathalie
%A FABLET, Ronan
%A Passat, Nicolas
%A Rousseau, François
%< avec comité de lecture
%B International Symposium on Biomedical Imaging (ISBI)
%C Venice, Italy
%8 2019
%D 2019
%K segmentation
%K super-resolution
%K neonatal brain MRI
%K 3D generative adversarial networks
%Z Computer Science [cs]/Artificial Intelligence [cs.AI]
%Z Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
%Z Computer Science [cs]/Medical ImagingConference papers
%X The analysis of clinical neonatal brain MRI remains challenging due to low anisotropic resolution of the data. In most pipelines, images are first re-sampled using interpolation or single image super-resolution techniques and then segmented using (semi-)automated approaches. Image reconstruction and segmentation are then performed separately. In this paper, we propose an end-to-end generative adversarial network for simultaneous high-resolution reconstruction and segmentation of brain MRI data. This joint approach is first assessed on the simulated low-resolution images of the high-resolution neonatal dHCP dataset. Then, the learned model is used to enhance and segment real clinical low-resolution images. Results demonstrate the potential of our proposed method with respect to practical medical applications.
%G English
%L hal-01895163
%U https://hal.archives-ouvertes.fr/hal-01895163
%~ CNRS
%~ UNIV-UBS
%~ UNIV-BREST
%~ CRESTIC
%~ INSTITUT-TELECOM
%~ ENIB
%~ LAB-STICC
%~ URCA
%~ LATIM
%~ IMT-ATLANTIQUE
%~ IMTA_ITI
%~ IMTA_SC
%~ LAB-STICC_IMTA
%~ LATIM_IMTA
%~ IBSAM
Communication dans un congrès
Hajji Zahran, Amis Cavalec Karine, Aissa El Bey Abdeldjalil
Joint channel estimation and simplicity-based detection for large-scale MIMO FEC-coded systems
10th International Symposium on Turbo Codes & Iterative Information Processing (ISTC), Dec 2018, Honk-Kong, Hong Kong SAR China. Proceedings 10th International Symposium on Turbo Codes & Iterative Information Processing (ISTC), 2018
Bibtext :
@inproceedings{hajji:hal-01893584,
TITLE = {{Joint channel estimation and simplicity-based detection for large-scale MIMO FEC-coded systems}},
AUTHOR = {Hajji, Zahran and Amis Cavalec, Karine and Aissa El Bey, Abdeldjalil},
URL = {https://hal.archives-ouvertes.fr/hal-01893584},
BOOKTITLE = {{10th International Symposium on Turbo Codes \& Iterative Information Processing (ISTC)}},
ADDRESS = {Honk-Kong, Hong Kong SAR China},
HAL_LOCAL_REFERENCE = {19247},
PAGES = {.},
YEAR = {2018},
MONTH = Dec,
KEYWORDS = {Channel estimation ; Simplicity ; Massive MIMO ; Turbo-detection},
PDF = {https://hal.archives-ouvertes.fr/hal-01893584/file/1570474591.pdf},
HAL_ID = {hal-01893584},
HAL_VERSION = {v1},
}
Endnote :
%0 Conference Proceedings
%T Joint channel estimation and simplicity-based detection for large-scale MIMO FEC-coded systems
%+ Lab-STICC_IMTA_CACS_COM
%+ Département Signal et Communications (SC)
%A Hajji, Zahran
%A Amis Cavalec, Karine
%A Aissa El Bey, Abdeldjalil
%< avec comité de lecture
%Z 19247
%( Proceedings 10th International Symposium on Turbo Codes & Iterative Information Processing (ISTC)
%B 10th International Symposium on Turbo Codes & Iterative Information Processing (ISTC)
%C Honk-Kong, Hong Kong SAR China
%P .
%8 2018-12-03
%D 2018
%K Channel estimation
%K Simplicity
%K Massive MIMO
%K Turbo-detection
%Z Engineering Sciences [physics]/Signal and Image processingConference papers
%X In this paper, we address the problem of channel estimation and signal detection in large MIMO FEC-coded systems assuming finite alphabet modulations. We consider a semi-blind iterative expectation maximization algorithm which relies on a limited number of pilot sequences to initialize the estimation process. We propose to include the estimation process within a turbo finite-alphabet simplicity (FAS)-based detection receiver. To that purpose we define two estimation updates from the FEC decoder output. Simulations carried out in both determined and undetermined configurations show that the resulting scheme outperforms the state-of-the-art receiver which uses an MMSE estimation criterion and that it reaches the maximum-likelihood lower-bound.
%G English
%2 https://hal.archives-ouvertes.fr/hal-01893584/document
%2 https://hal.archives-ouvertes.fr/hal-01893584/file/1570474591.pdf
%L hal-01893584
%U https://hal.archives-ouvertes.fr/hal-01893584
%~ TELECOM-BRETAGNE
%~ INSTITUT-TELECOM
%~ CNRS
%~ UNIV-BREST
%~ UNIV-UBS
%~ ENIB
%~ LAB-STICC
%~ IMT-ATLANTIQUE
%~ LAB-STICC_IMTA_CACS_COM
%~ IMTA_SC
%~ LAB-STICC_IMTA
Communication dans un congrès
Hmamouche Yassine, Benjillali Mustapha, Saoudi Samir
Closed-form Coverage Probability under the Idle Mode Capability: A Stochastic Geometry Approach
ISIVC 2018, International Symposium on Signal Image Video and Communications, Nov 2018, rabat, Morocco
Bibtext :
@inproceedings{hmamouche:hal-01893752,
TITLE = {{Closed-form Coverage Probability under the Idle Mode Capability: A Stochastic Geometry Approach}},
AUTHOR = {Hmamouche, Yassine and Benjillali, Mustapha and Saoudi, Samir},
URL = {https://hal.archives-ouvertes.fr/hal-01893752},
BOOKTITLE = {{ISIVC 2018, International Symposium on Signal Image Video and Communications}},
ADDRESS = {rabat, Morocco},
YEAR = {2018},
MONTH = Nov,
PDF = {https://hal.archives-ouvertes.fr/hal-01893752/file/ISIVC_2018_paper_42.pdf},
HAL_ID = {hal-01893752},
HAL_VERSION = {v1},
}
Endnote :
%0 Conference Paper
%F Oral
%T Closed-form Coverage Probability under the Idle Mode Capability: A Stochastic Geometry Approach
%+ Lab-STICC_IMTA_CACS_COM
%+ Département Signal et Communications (SC)
%+ Institut National de Postes et Télécommunications [Rabat] (INPT)
%A Hmamouche, Yassine
%A Benjillali, Mustapha
%A Saoudi, Samir
%< avec comité de lecture
%B ISIVC 2018, International Symposium on Signal Image Video and Communications
%C rabat, Morocco
%8 2018-11-27
%D 2018
%Z Engineering Sciences [physics]Conference papers
%X In this paper, we provide a comprehensive overview of the stochastic geometry framework explored extensively in literature to model and analyze the performance of communication networks. We provide a brief survey of the history of the approach, including recent applications to the analysis of several 5G enabling technologies. In the main technical section of the paper, we consider a case study in which we assume a system model where the idle mode capability is activated on base stations. A general expression of the coverage probability based on hypergeometric functions is then derived, yielding closed-form expressions that depend on the parity of the path loss exponent. Numerical results confirm the accuracy of our practical approximations.
%G English
%2 https://hal.archives-ouvertes.fr/hal-01893752/document
%2 https://hal.archives-ouvertes.fr/hal-01893752/file/ISIVC_2018_paper_42.pdf
%L hal-01893752
%U https://hal.archives-ouvertes.fr/hal-01893752
%~ CNRS
%~ UNIV-BREST
%~ UNIV-UBS
%~ INSTITUT-TELECOM
%~ ENIB
%~ LAB-STICC
%~ IMT-ATLANTIQUE
%~ LAB-STICC_IMTA_CACS_COM
%~ IMTA_SC
%~ LAB-STICC_IMTA
Communication dans un congrès
Mai Van Khanh, Pastor Dominique, Aissa El Bey Abdeldjalil
Block Smoothed Sigmoid-Based Shrinkage in Time-Frequency Domain for Robust Audio Denoising
9th International Symposium on Signal, Image, Video and Communications (ISIVC), Nov 2018, Rabat, Morocco. Proceedings 9th International Symposium on Signal, Image, Video and Communications (ISIVC), 2018
Bibtext :
@inproceedings{mai:hal-01893712,
TITLE = {{Block Smoothed Sigmoid-Based Shrinkage in Time-Frequency Domain for Robust Audio Denoising}},
AUTHOR = {Mai, Van Khanh and Pastor, Dominique and Aissa El Bey, Abdeldjalil},
URL = {https://hal.archives-ouvertes.fr/hal-01893712},
BOOKTITLE = {{9th International Symposium on Signal, Image, Video and Communications (ISIVC)}},
ADDRESS = {Rabat, Morocco},
HAL_LOCAL_REFERENCE = {19255},
PAGES = {.},
YEAR = {2018},
MONTH = Nov,
KEYWORDS = {Block threshold ; Audio denoising ; Smoothed sigmoid-based shrinkage},
PDF = {https://hal.archives-ouvertes.fr/hal-01893712/file/PID5583835.pdf},
HAL_ID = {hal-01893712},
HAL_VERSION = {v1},
}
Endnote :
%0 Conference Proceedings
%T Block Smoothed Sigmoid-Based Shrinkage in Time-Frequency Domain for Robust Audio Denoising
%+ Département Signal et Communications (SC)
%+ Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC)
%+ Lab-STICC_IMTA_CID_TOMS
%+ Lab-STICC_IMTA_CACS_COM
%A Mai, Van Khanh
%A Pastor, Dominique
%A Aissa El Bey, Abdeldjalil
%< avec comité de lecture
%Z 19255
%( Proceedings 9th International Symposium on Signal, Image, Video and Communications (ISIVC)
%B 9th International Symposium on Signal, Image, Video and Communications (ISIVC)
%C Rabat, Morocco
%P .
%8 2018-11-27
%D 2018
%K Block threshold
%K Audio denoising
%K Smoothed sigmoid-based shrinkage
%Z Engineering Sciences [physics]/Signal and Image processingConference papers
%X In this paper, we propose a novel robust method for short-time spectral amplitude (STSA) estimation in audio denoising. This method extends the smoothed sigmoid-based shrinkage (SSBS), which does not require any prior information about the probability distribution of the signal of interest. With regard to audio processing, the SSBS method yields better performance in terms of noise reduction but nevertheless introduces significant musical noise. In order to benefit from non-diagonal processing, which removes background noise without introducing musical noise, two non-diagonal SSBS are derived. First, the decision directed approach is incorporated into the SSBS method. Second, the time-frequency domain is divided into rectangular blocks and then, a SSBS function is applied to estimate the spectral amplitude in each block. The experimental results demonstrate the relevance of the proposed methods both in terms of speech quality and intelligibility via objective criteria.
%G English
%2 https://hal.archives-ouvertes.fr/hal-01893712/document
%2 https://hal.archives-ouvertes.fr/hal-01893712/file/PID5583835.pdf
%L hal-01893712
%U https://hal.archives-ouvertes.fr/hal-01893712
%~ TELECOM-BRETAGNE
%~ INSTITUT-TELECOM
%~ CNRS
%~ UNIV-BREST
%~ UNIV-UBS
%~ ENIB
%~ LAB-STICC
%~ IMT-ATLANTIQUE
%~ LAB-STICC_IMTA_CID_TOMS
%~ LAB-STICC_IMTA_CACS_COM
%~ IMTA_SC
%~ LAB-STICC_IMTA
Communication dans un congrès
Mai Van Khanh, Pastor Dominique, Aissa El Bey Abdeldjalil
Joint Soft Threshold and Statistical Estimation for Speech Enhancement
9th International Symposium on Signal, Image, Video and Communications (ISIVC), Nov 2018, Rabat, Morocco. Proceedings 9th International Symposium on Signal, Image, Video and Communications (ISIVC), 2018
Bibtext :
@inproceedings{mai:hal-01893685,
TITLE = {{Joint Soft Threshold and Statistical Estimation for Speech Enhancement}},
AUTHOR = {Mai, Van Khanh and Pastor, Dominique and Aissa El Bey, Abdeldjalil},
URL = {https://hal.archives-ouvertes.fr/hal-01893685},
BOOKTITLE = {{9th International Symposium on Signal, Image, Video and Communications (ISIVC)}},
ADDRESS = {Rabat, Morocco},
HAL_LOCAL_REFERENCE = {19254},
PAGES = {.},
YEAR = {2018},
MONTH = Nov,
KEYWORDS = {Sigmoid shrinkage ; MMSE ; Speech enhancement ; Noise reduction},
PDF = {https://hal.archives-ouvertes.fr/hal-01893685/file/PID5584289.pdf},
HAL_ID = {hal-01893685},
HAL_VERSION = {v1},
}
Endnote :
%0 Conference Proceedings
%T Joint Soft Threshold and Statistical Estimation for Speech Enhancement
%+ Département Signal et Communications (SC)
%+ Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC)
%+ Lab-STICC_IMTA_CID_TOMS
%+ Lab-STICC_IMTA_CACS_COM
%A Mai, Van Khanh
%A Pastor, Dominique
%A Aissa El Bey, Abdeldjalil
%< avec comité de lecture
%Z 19254
%( Proceedings 9th International Symposium on Signal, Image, Video and Communications (ISIVC)
%B 9th International Symposium on Signal, Image, Video and Communications (ISIVC)
%C Rabat, Morocco
%P .
%8 2018-11-27
%D 2018
%K Sigmoid shrinkage
%K MMSE
%K Speech enhancement
%K Noise reduction
%Z Engineering Sciences [physics]/Signal and Image processingConference papers
%X This paper presents a novel method for speech enhancement based on the combination of sigmoid shrinkage and bayesian estimator. The main idea is to apply a joint detection and estimation to noisy speech before using a standard minimum-mean-squared-error (MMSE) estimator. Hence, the proposed method can take advantage of two basic approaches for improving the quality of noisy speech. Experiments performed on stationary and non-stationary noisy speech signals show that the proposed approach is promising when compared to classical methods, in terms of objective and pseudo-subjective measurements.
%G English
%2 https://hal.archives-ouvertes.fr/hal-01893685/document
%2 https://hal.archives-ouvertes.fr/hal-01893685/file/PID5584289.pdf
%L hal-01893685
%U https://hal.archives-ouvertes.fr/hal-01893685
%~ TELECOM-BRETAGNE
%~ INSTITUT-TELECOM
%~ CNRS
%~ UNIV-BREST
%~ UNIV-UBS
%~ ENIB
%~ LAB-STICC
%~ IMT-ATLANTIQUE
%~ LAB-STICC_IMTA_CID_TOMS
%~ LAB-STICC_IMTA_CACS_COM
%~ IMTA_SC
%~ LAB-STICC_IMTA
Article dans une revue
Ouala Said, Fablet Ronan, Herzet Cédric, Chapron Bertrand, Pascual Ananda, Collard Fabrice, Gaultier Lucile
Neural-Network-based Kalman Filters for the Spatio-Temporal Interpolation of Satellite-derived Sea Surface Temperature
Remote Sensing, MDPI, 2018
Bibtext :
@article{ouala:hal-01896654,
TITLE = {{Neural-Network-based Kalman Filters for the Spatio-Temporal Interpolation of Satellite-derived Sea Surface Temperature}},
AUTHOR = {Ouala, Said and FABLET, Ronan and Herzet, C{\'e}dric and Chapron, Bertrand and Pascual, Ananda and Collard, Fabrice and Gaultier, Lucile},
URL = {https://hal-imt-atlantique.archives-ouvertes.fr/hal-01896654},
JOURNAL = {{Remote Sensing}},
PUBLISHER = {{MDPI}},
YEAR = {2018},
MONTH = Nov,
KEYWORDS = {Data-driven ; Neural networks ; Kalman filter ; Data assimilation ; Dynamical model},
PDF = {https://hal-imt-atlantique.archives-ouvertes.fr/hal-01896654/file/S.OUALA_Paper.pdf},
HAL_ID = {hal-01896654},
HAL_VERSION = {v1},
}
Endnote :
%0 Journal Article
%T Neural-Network-based Kalman Filters for the Spatio-Temporal Interpolation of Satellite-derived Sea Surface Temperature
%+ Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC)
%+ Département Signal et Communications (SC)
%+ SIMulation pARTiculaire de Modèles Stochastiques (SIMSMART)
%+ Laboratoire d’Oéanographie Spatiale [Plouzané] (LOS)
%+ Institut Mediterrani d'Estudis Avancats (IMEDEA)
%+ OceanDataLab
%A Ouala, Said
%A FABLET, Ronan
%A Herzet, Cédric
%A Chapron, Bertrand
%A Pascual, Ananda
%A Collard, Fabrice
%A Gaultier, Lucile
%< avec comité de lecture
%@ 2072-4292
%J Remote Sensing
%I MDPI
%8 2018-11-10
%D 2018
%K Data-driven
%K Neural networks
%K Kalman filter
%K Data assimilation
%K Dynamical model
%Z Environmental Sciences
%Z Mathematics [math]/Statistics [math.ST]
%Z Mathematics [math]/Dynamical Systems [math.DS]Journal articles
%X In this work we address the reconstruction of gap-free Sea Surface Temperature (SST) fields 1 from irregularly-sampled satellite-derived observations. We develop novel Neural-Network-based 2 (NN-based) Kalman filters for spatio-temporal interpolation issues as an alternative to ensemble 3 Kalman filters (EnKF). The key features of the proposed approach are twofold: the learning of 4 a probabilistic NN-based representation of 2D geophysical dynamics, the associated parametric 5 Kalman-like filtering scheme for a computationally-efficient spatio-temporal interpolation of Sea 6 Surface Temperature (SST) fields. We illustrate the relevance of our contribution for an OSSE 7 (Observing System Simulation Experiment) in a case-study region off South Africa. Our numerical 8 experiments report significant improvements in terms of reconstruction performance compared with 9 operational and state-of-the-art schemes (e.g., optimal interpolation, Empirical Orthogonal Function 10 (EOF) based interpolation and analog data assimilation).
%G English
%2 https://hal-imt-atlantique.archives-ouvertes.fr/hal-01896654/document
%2 https://hal-imt-atlantique.archives-ouvertes.fr/hal-01896654/file/S.OUALA_Paper.pdf
%L hal-01896654
%U https://hal-imt-atlantique.archives-ouvertes.fr/hal-01896654
%~ IMT-ATLANTIQUE
%~ CNRS
%~ UNIV-BREST
%~ UNIV-UBS
%~ IFREMER
%~ INRIA-RENNES
%~ SDE
%~ INSMI
%~ INSTITUT-TELECOM
%~ UNAM
%~ ENIB
%~ TDS-MACS
%~ LAB-STICC
%~ UNIV-RENNES1
%~ INRIA_TEST
%~ CHL
%~ GIP-BE
%~ AGREENIUM
%~ UNIV-RENNES2
%~ UR2-HB
%~ INRIA
%~ TEST-UR-CSS
%~ LAB-STICC_IMTA
%~ UNIV-RENNES
%~ INRIA-RENGRE
%~ IRMAR
%~ IMTA_SC
%~ UR1-MATH-STIC
%~ UR1-HAL
%~ INSA-GROUPE
Article dans une revue
Meziane Bentahar Meziane Abdelfettah, Chonavel Thierry, Aissa El Bey Abdeldjalil, Belouchrani Adel
An analytical derivation for second-order blind separation of two signals
Annals of Telecommunications - annales des télécommunications, Springer, 2018, 73 (11), pp.711 - 717. 〈10.1007/s12243-018-0635-6〉
Bibtext :
@article{mezianebentaharmeziane:hal-01770936,
TITLE = {{An analytical derivation for second-order blind separation of two signals}},
AUTHOR = {Meziane Bentahar Meziane, Abdelfettah and Chonavel, Thierry and Aissa El Bey, Abdeldjalil and Belouchrani, Adel},
URL = {https://hal.archives-ouvertes.fr/hal-01770936},
JOURNAL = {{Annals of Telecommunications - annales des t{\'e}l{\'e}communications}},
HAL_LOCAL_REFERENCE = {18866},
PUBLISHER = {{Springer}},
VOLUME = {73},
NUMBER = {11},
PAGES = {711 - 717},
YEAR = {2018},
MONTH = Nov,
DOI = {10.1007/s12243-018-0635-6},
KEYWORDS = {Blind source separation ; Second order statistics ; TITO systems},
PDF = {https://hal.archives-ouvertes.fr/hal-01770936/file/SOBAS_Annals_Telecom.pdf},
HAL_ID = {hal-01770936},
HAL_VERSION = {v1},
}
Endnote :
%0 Journal Article
%T An analytical derivation for second-order blind separation of two signals
%+ Ecole Nationale Polytechnique [Alger] (ENP)
%+ Lab-STICC_IMTA_CID_TOMS
%+ Département Signal et Communications (SC)
%+ Lab-STICC_IMTA_CACS_COM
%A Meziane Bentahar Meziane, Abdelfettah
%A Chonavel, Thierry
%A Aissa El Bey, Abdeldjalil
%A Belouchrani, Adel
%< avec comité de lecture
%Z 18866
%@ 0003-4347
%J Annals of Telecommunications - annales des télécommunications
%I Springer
%V 73
%N 11
%P 711 - 717
%8 2018-11
%D 2018
%R 10.1007/s12243-018-0635-6
%K Blind source separation
%K Second order statistics
%K TITO systems
%Z Engineering Sciences [physics]/Signal and Image processingJournal articles
%X In this paper, we propose analytical formulas that involve second-order statistics for separating two signals. The method utilizes source decorrelation and correlation function diversity. In particular, the proposed SOBAS (Second-Order Blind Analytical Separation) algorithm differs from the ASOBI (Analytical Second-Order Blind Identification) algorithm in that it does not require prior knowledge or estimation of the noise variance. Computer simulations demonstrate the effectiveness of the proposed method.
%G English
%2 https://hal.archives-ouvertes.fr/hal-01770936/document
%2 https://hal.archives-ouvertes.fr/hal-01770936/file/SOBAS_Annals_Telecom.pdf
%L hal-01770936
%U https://hal.archives-ouvertes.fr/hal-01770936
%~ CNRS
%~ UNIV-UBS
%~ INSTITUT-TELECOM
%~ ENIB
%~ LAB-STICC
%~ UNIV-BREST
%~ LAB-STICC_IMTA_CACS_COM
%~ LAB-STICC_IMTA_CID_TOMS
%~ IMTA_SC
%~ IMT-ATLANTIQUE
%~ LAB-STICC_IMTA
Communication dans un congrès
Lassami Nacerredine, Aissa El Bey Abdeldjalil, Abed-Meraim Karim
Adaptive Blind Identification of Sparse SIMO Channels using Maximum a Posteriori Approach
Asilomar Conference on Signals, Systems, and Computers, Oct 2018, Pacific Grove, Ca, United States. Proceedings Asilomar Conference on Signals, Systems, and Computers, 2018
Bibtext :
@inproceedings{lassami:hal-01847560,
TITLE = {{Adaptive Blind Identification of Sparse SIMO Channels using Maximum a Posteriori Approach}},
AUTHOR = {Lassami, Nacerredine and Aissa El Bey, Abdeldjalil and Abed-Meraim, Karim},
URL = {https://hal.archives-ouvertes.fr/hal-01847560},
BOOKTITLE = {{Asilomar Conference on Signals, Systems, and Computers}},
ADDRESS = {Pacific Grove, Ca, United States},
HAL_LOCAL_REFERENCE = {19096},
PAGES = {.},
YEAR = {2018},
MONTH = Oct,
KEYWORDS = {Adaptive algorithms ; Sparse channel ; SIMO channel ; Blind identification},
PDF = {https://hal.archives-ouvertes.fr/hal-01847560/file/adaptive-blind-identification.pdf},
HAL_ID = {hal-01847560},
HAL_VERSION = {v1},
}
Endnote :
%0 Conference Proceedings
%T Adaptive Blind Identification of Sparse SIMO Channels using Maximum a Posteriori Approach
%+ Lab-STICC_IMTA_CACS_COM
%+ Département Signal et Communications (SC)
%+ Laboratoire Pluridisciplinaire de Recherche en Ingénierie des Systèmes, Mécanique et Energétique (PRISME)
%A Lassami, Nacerredine
%A Aissa El Bey, Abdeldjalil
%A Abed-Meraim, Karim
%< avec comité de lecture
%Z 19096
%( Proceedings Asilomar Conference on Signals, Systems, and Computers
%B Asilomar Conference on Signals, Systems, and Computers
%C Pacific Grove, Ca, United States
%P .
%8 2018-10-28
%D 2018
%K Adaptive algorithms
%K Sparse channel
%K SIMO channel
%K Blind identification
%Z Engineering Sciences [physics]/Signal and Image processingConference papers
%X In this paper, we are interested in adaptive blind channel identification of sparse single input multiple output (SIMO) systems. A generalized Laplacian distribution is considered to enhance the sparsity of the channel coefficients with a maximum a posteriori (MAP) approach. The resulting cost function is composed of the classical deterministic maximum likelihood (ML) term and an additive $\ell_p$ norm of the channel coefficient vector which represents the sparsity penalization. The proposed adaptive optimization algorithm is based on a simple gradient step. Simulations show that our method outperforms the existing adaptive versions of cross-relation (CR) method.
%G English
%2 https://hal.archives-ouvertes.fr/hal-01847560/document
%2 https://hal.archives-ouvertes.fr/hal-01847560/file/adaptive-blind-identification.pdf
%L hal-01847560
%U https://hal.archives-ouvertes.fr/hal-01847560
%~ TELECOM-BRETAGNE
%~ INSTITUT-TELECOM
%~ CNRS
%~ UNIV-UBS
%~ ENSI-BOURGES
%~ MSL
%~ MSL-THESE
%~ ENIB
%~ LAB-STICC
%~ UNIV-BREST
%~ UNIV-ORLEANS
%~ IMT-ATLANTIQUE
%~ IMTA_SC
%~ LAB-STICC_IMTA_CACS_COM
%~ PRISME-CVL
%~ LAB-STICC_IMTA
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