Abdeldjalil AISSA EL BEY

Poste

Enseignant chercheur

Département

Département Signal et Communication

Localisation

Brest

Coordonnées :

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+33 2 29 00 15 72
Publications HAL
Article dans une revue
Boashash Boualem, Aissa El Bey Abdeldjalil
Robust multisensor time-frequency signal processing: A tutorial review with illustrations of performance enhancement in selected application areas
Digital Signal Processing, Elsevier, 2018, 77, pp.153-186. 〈10.1016/j.dsp.2017.11.017〉
Bibtext :
@article{boashash:hal-01770948,
TITLE = {{Robust multisensor time-frequency signal processing: A tutorial review with illustrations of performance enhancement in selected application areas}},
AUTHOR = {Boashash, Boualem and Aissa El Bey, Abdeldjalil},
URL = {https://hal.archives-ouvertes.fr/hal-01770948},
JOURNAL = {{Digital Signal Processing}},
HAL_LOCAL_REFERENCE = {18447},
PUBLISHER = {{Elsevier}},
VOLUME = {77},
PAGES = {.153-186},
YEAR = {2018},
MONTH = Jun,
DOI = {10.1016/j.dsp.2017.11.017},
KEYWORDS = {EEG abnormality source localization ; Time-frequency analysis ; High-resolution TFDs ; Multisensor TFDs ; Direction of arrival ; Blind source separation ; Lead field matrix ; Non-stationary array processing},
HAL_ID = {hal-01770948},
HAL_VERSION = {v1},
}
Endnote :
%0 Journal Article
%T Robust multisensor time-frequency signal processing: A tutorial review with illustrations of performance enhancement in selected application areas
%+ Qatar University
%+ Lab-STICC_IMTA_CACS_COM
%+ Département Signal et Communications (SC)
%A Boashash, Boualem
%A Aissa El Bey, Abdeldjalil
%< avec comité de lecture
%Z 18447
%@ 1051-2004
%J Digital Signal Processing
%I Elsevier
%V 77
%P .153-186
%8 2018-06
%D 2018
%R 10.1016/j.dsp.2017.11.017
%K EEG abnormality source localization
%K Time-frequency analysis
%K High-resolution TFDs
%K Multisensor TFDs
%K Direction of arrival
%K Blind source separation
%K Lead field matrix
%K Non-stationary array processing
%Z Engineering Sciences [physics]/Signal and Image processingJournal articles
%X This paper presents high-resolution multisensor time-frequency distributions (MTFDs) and their applications to the analysis of multichannel non-stationary signals. The approach combines high-resolution time-frequency analysis and array signal processing methods. The improved performance of MTFDs is demonstrated using several applications including source localization based on direction of arrival (DOA) estimation and automated component separation (ACS) of non-stationary sources, with focus on blind source separation. The MTFD approach is further illustrated by two applications to EEG signals. One specifically uses ACS and DOA estimation methods for artifacts removal and source localization. Another uses MTFDs for cross-channel causality analysis. Data and code are provided to allow readers to reproduce the results presented, and apply these methods to their own data.
%G English
%L hal-01770948
%U https://hal.archives-ouvertes.fr/hal-01770948
%~ CNRS
%~ UNIV-UBS
%~ INSTITUT-TELECOM
%~ ENIB
%~ LAB-STICC
%~ UNIV-BREST
%~ LAB-STICC_IMTA_CACS_COM
%~ IMTA_SC
%~ IMT-ATLANTIQUE
%~ LAB-STICC_IMTA
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, 〈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}},
PAGES = {.},
YEAR = {2018},
MONTH = May,
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
%P .
%8 2018-05
%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
Article dans une revue
Boashash Boualem, Aissa El Bey Abdeldjalil, Al-Sa'D Mohammad Fathi
Multisensor Time-Frequency Signal Processing Software Matlab Package: An analysis tool for multichannel non-stationary data
Bibtext :
@article{boashash:hal-01770937,
TITLE = {{Multisensor Time-Frequency Signal Processing Software Matlab Package: An analysis tool for multichannel non-stationary data}},
AUTHOR = {Boashash, Boualem and Aissa El Bey, Abdeldjalil and Al-Sa'D, Mohammad Fathi},
URL = {https://hal.archives-ouvertes.fr/hal-01770937},
JOURNAL = {{SoftwareX}},
HAL_LOCAL_REFERENCE = {18696},
PAGES = {.},
YEAR = {2018},
MONTH = Apr,
DOI = {10.1016/j.softx.2017.12.002},
KEYWORDS = {Multisensor time--frequency analysis ; Direction of arrival ; Automated component separation ; Blind source separation ; Non-stationary array processing ; Cross-channel causality analysis},
HAL_ID = {hal-01770937},
HAL_VERSION = {v1},
}
Endnote :
%0 Journal Article
%T Multisensor Time-Frequency Signal Processing Software Matlab Package: An analysis tool for multichannel non-stationary data
%+ Qatar University
%+ Lab-STICC_IMTA_CACS_COM
%+ Département Signal et Communications (SC)
%A Boashash, Boualem
%A Aissa El Bey, Abdeldjalil
%A Al-Sa'D, Mohammad Fathi
%< avec comité de lecture
%Z 18696
%J SoftwareX
%P .
%8 2018-04
%D 2018
%R 10.1016/j.softx.2017.12.002
%K Multisensor time–frequency analysis
%K Direction of arrival
%K Automated component separation
%K Blind source separation
%K Non-stationary array processing
%K Cross-channel causality analysis
%Z Engineering Sciences [physics]/Signal and Image processingJournal articles
%X The Multisensor Time-Frequency Signal Processing (MTFSP) Matlab package is an analysis tool for multichannel non-stationary signals collected from an array of sensors. By combining array signal processing for non-stationary signals and multichannel high resolution time-frequency methods, MTFSP enables applications such as cross-channel causality relationships, automated component separation and direction of arrival estimation, using multisensor time-frequency distributions (MTFDs). MTFSP can address old and new applications such as: abnormality detection in biomedical signals, source localization in wireless communications or condition monitoring and fault detection in industrial plants. It allows e.g. the reproduction of the results presented in [3].
%G English
%L hal-01770937
%U https://hal.archives-ouvertes.fr/hal-01770937
%~ CNRS
%~ UNIV-UBS
%~ INSTITUT-TELECOM
%~ ENIB
%~ LAB-STICC
%~ UNIV-BREST
%~ LAB-STICC_IMTA_CACS_COM
%~ IMTA_SC
%~ IMT-ATLANTIQUE
%~ LAB-STICC_IMTA
Article dans une revue
Messai Malek, Aïssa-El-Bey Abdeldjalil, Amis Cavalec Karine, Guilloud Frédéric
Improved sparse multiuser detection based on modulation-alphabets exploitation
Digital Signal Processing, Elsevier, 2017, 71, pp.27 - 35. 〈10.1016/j.dsp.2017.08.011〉
Bibtext :
@article{messai:hal-01609983,
TITLE = {{Improved sparse multiuser detection based on modulation-alphabets exploitation}},
AUTHOR = {Messai, Malek and A{\"i}ssa-El-Bey, Abdeldjalil and Amis Cavalec, Karine and GUILLOUD, Fr{\'e}d{\'e}ric},
URL = {https://hal.archives-ouvertes.fr/hal-01609983},
JOURNAL = {{Digital Signal Processing}},
HAL_LOCAL_REFERENCE = {18192},
PUBLISHER = {{Elsevier}},
VOLUME = {71},
PAGES = {27 - 35},
YEAR = {2017},
MONTH = Dec,
DOI = {10.1016/j.dsp.2017.08.011},
KEYWORDS = {Compressed sensing ; Group orthogonal matching pursuit ; L1-minimization ; Sparsity ; Multi-user detection ; Sporadic communication},
HAL_ID = {hal-01609983},
HAL_VERSION = {v1},
}
Endnote :
%0 Journal Article
%T Improved sparse multiuser detection based on modulation-alphabets exploitation
%+ Département Signal et Communications (SC)
%+ Lab-STICC_IMTA_CACS_COM
%A Messai, Malek
%A Aïssa-El-Bey, Abdeldjalil
%A Amis Cavalec, Karine
%A GUILLOUD, Frédéric
%< avec comité de lecture
%Z 18192
%@ 1051-2004
%J Digital Signal Processing
%I Elsevier
%V 71
%P 27 - 35
%8 2017-12
%D 2017
%R 10.1016/j.dsp.2017.08.011
%K Compressed sensing
%K Group orthogonal matching pursuit
%K L1-minimization
%K Sparsity
%K Multi-user detection
%K Sporadic communication
%Z Engineering Sciences [physics]/Signal and Image processingJournal articles
%X In this paper, we focus on sporadic random-access communications and consider compressed-sensing (CS) techniques to perform the multiuser detection (MUD). Since all the users do not necessarily transmit information, MUD consists in detecting the transmitting users (activity detection) and their corresponding transmitted data (data detection). The main results presented here rely on the exploitation of the user signal alphabet knowledge within the detection step. To this aim, several modifications of the group orthogonal matching pursuit (GOMP) algorithm were proposed, differing in the way the modulation alphabet knowledge is considered within the detection stage. These modifications can be extended to any greedy-based CS-MUD. To overcome the error floor occurring at high SNR with a higher number of active users, we then propose an iterative minimization-based MUD algorithm that alternates between activity and data detection. Compared to the existing GOMP-based CS-MUD, the proposed modified GOMP algorithms exhibit a significant gain with almost the same complexity. The iterative minimization-based MUD algorithm has a higher complexity but outperforms all the others without any observed error-floor.
%G English
%L hal-01609983
%U https://hal.archives-ouvertes.fr/hal-01609983
%~ TELECOM-BRETAGNE
%~ INSTITUT-TELECOM
%~ CNRS
%~ UNIV-UBS
%~ ENIB
%~ LAB-STICC
%~ UNIV-BREST
%~ IMTA_SC
%~ LAB-STICC_IMTA_CACS_COM
%~ IMT-ATLANTIQUE
%~ LAB-STICC_IMTA
Article dans une revue
Ouelha Samir, Aïssa-El-Bey Abdeldjalil, Boashash Boualem
Improving DOA Estimation Algorithms using High-Resolution Quadratic Time-Frequency Distributions
IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, 2017, 65 (19), pp.5179 - 5190. 〈10.1109/TSP.2017.2718974〉
Bibtext :
@article{ouelha:hal-01609986,
TITLE = {{Improving DOA Estimation Algorithms using High-Resolution Quadratic Time-Frequency Distributions}},
AUTHOR = {Ouelha, Samir and A{\"i}ssa-El-Bey, Abdeldjalil and Boashash, Boualem},
URL = {https://hal.archives-ouvertes.fr/hal-01609986},
JOURNAL = {{IEEE Transactions on Signal Processing}},
HAL_LOCAL_REFERENCE = {17956},
PUBLISHER = {{Institute of Electrical and Electronics Engineers}},
VOLUME = {65},
NUMBER = {19},
PAGES = {5179 - 5190},
YEAR = {2017},
MONTH = Oct,
DOI = {10.1109/TSP.2017.2718974},
KEYWORDS = {Time-frequency distribution ; High-resolution TFDs ; Spatial TFDs ; Blind source separation ; Direction of arrival estimation},
HAL_ID = {hal-01609986},
HAL_VERSION = {v1},
}
Endnote :
%0 Journal Article
%T Improving DOA Estimation Algorithms using High-Resolution Quadratic Time-Frequency Distributions
%+ Qatar University
%+ Lab-STICC_IMTA_CACS_COM
%+ Département Signal et Communications (SC)
%A Ouelha, Samir
%A Aïssa-El-Bey, Abdeldjalil
%A Boashash, Boualem
%< avec comité de lecture
%Z 17956
%@ 1053-587X
%J IEEE Transactions on Signal Processing
%I Institute of Electrical and Electronics Engineers
%V 65
%N 19
%P 5179 - 5190
%8 2017-10
%D 2017
%R 10.1109/TSP.2017.2718974
%K Time-frequency distribution
%K High-resolution TFDs
%K Spatial TFDs
%K Blind source separation
%K Direction of arrival estimation
%Z Engineering Sciences [physics]/Signal and Image processingJournal articles
%X This paper addresses the problem of direction of arrival (DOA) estimation and blind source separation (BSS) for non-stationary signals in the underdetermined case. These two problems are strongly related to the mixing matrix estimation problem. To deal with the non-stationary characteristics of signals, this study uses high-resolution quadratic time-frequency distributions (TFDs) to reduce the cross-terms while keeping a good resolution for the construction of the spatial TFDs (STFDs). The main contributions of this paper are (1) the formulation of a statistical test for the noise thresholding step to improve robustness and avoid the use of empirical parameters; this test performs multisource selection of the time-frequency points where the signal of interest is present; (2) the use of an algorithm, based on image processing methods, which performs an auto-source selection for mixing matrix estimation. The paper presents results on simulated signals that demonstrate an improvement of 10 dB in terms of normalized mean square error for BSS and 7% in terms of relative error for DOA estimation over standard methods.
%G English
%L hal-01609986
%U https://hal.archives-ouvertes.fr/hal-01609986
%~ INSTITUT-TELECOM
%~ TELECOM-BRETAGNE
%~ CNRS
%~ UNIV-UBS
%~ ENIB
%~ LAB-STICC
%~ UNIV-BREST
%~ IMTA_SC
%~ LAB-STICC_IMTA_CACS_COM
%~ IMT-ATLANTIQUE
%~ LAB-STICC_IMTA
Poster
Lopez Radcenco Manuel, Fablet Ronan, Aïssa-El-Bey Abdeldjalil, Ailliot Pierre
Non-negative Decomposition of Geophysical Dynamics
GODAE OceanView International School 2017, Oct 2017, Palma, Spain
Bibtext :
@misc{lopezradcenco:hal-01739801,
TITLE = {{Non-negative Decomposition of Geophysical Dynamics}},
AUTHOR = {Lopez Radcenco, Manuel and FABLET, Ronan and A{\"i}ssa-El-Bey, Abdeldjalil and Ailliot, Pierre},
URL = {https://hal.archives-ouvertes.fr/hal-01739801},
NOTE = {Poster},
HOWPUBLISHED = {{GODAE OceanView International School 2017}},
HAL_LOCAL_REFERENCE = {18861},
PAGES = {.},
YEAR = {2017},
MONTH = Oct,
KEYWORDS = {Non-negativity ; Dictionary learning ; Sea surface temperature ; Sea surface salinity ; Dynamical systems ; Super-resolution},
PDF = {https://hal.archives-ouvertes.fr/hal-01739801/file/lopez_radcenco_et_al_poster_gov_2017.pdf},
HAL_ID = {hal-01739801},
HAL_VERSION = {v1},
}
Endnote :
%0 Conference Paper
%F Poster
%T Non-negative Decomposition of Geophysical Dynamics
%+ Lab-STICC_IMTA_CID_TOMS
%+ Département Signal et Communications (SC)
%+ Lab-STICC_IMTA_CACS_COM
%+ Laboratoire de Mathématiques de Bretagne Atlantique (LMBA)
%A Lopez Radcenco, Manuel
%A FABLET, Ronan
%A Aïssa-El-Bey, Abdeldjalil
%A Ailliot, Pierre
%< sans comité de lecture
%Z 18861
%B GODAE OceanView International School 2017
%C Palma, Spain
%P .
%8 2017-10-01
%D 2017
%K Non-negativity
%K Dictionary learning
%K Sea surface temperature
%K Sea surface salinity
%K Dynamical systems
%K Super-resolution
%Z Engineering Sciences [physics]/Signal and Image processingPoster communications
%X The decomposition of geophysical processes into relevant modes is a key issue for characterization, forecasting and reconstruction problems in environmental sciences. Moreover, the blind separation of contributions associated with different sources is a classical problem in signal and image processing. Recently, significant advances have been reported with the introduction of non-negative and sparse formulations. In this work, we address the blind decomposition of linear operators or transfer functions between variables of interest, with an emphasis on a non-negative setting. We illustrate the relevance of these decompositions for the analysis, prediction and reconstruction of geophysical dynamics.
%G English
%2 https://hal.archives-ouvertes.fr/hal-01739801/document
%2 https://hal.archives-ouvertes.fr/hal-01739801/file/lopez_radcenco_et_al_poster_gov_2017.pdf
%L hal-01739801
%U https://hal.archives-ouvertes.fr/hal-01739801
%~ INSTITUT-TELECOM
%~ TELECOM-BRETAGNE
%~ CNRS
%~ UNIV-UBS
%~ MATHBREST
%~ LMBA
%~ ENIB
%~ LAB-STICC
%~ CHL
%~ UNIV-BREST
%~ LAB-STICC_IMTA_CACS_COM
%~ LAB-STICC_IMTA_CID_TOMS
%~ IMTA_SC
%~ IMT-ATLANTIQUE
%~ LAB-STICC_IMTA
Communication dans un congrès
Lopez Radcenco Manuel, Fablet Ronan, Aïssa-El-Bey Abdeldjalil, Ailliot Pierre
Locally-adapted convolution-based super-resolution of irregularly-sampled ocean remote sensing data
ICIP 2017 : IEEE International Conference on Image Processing, Sep 2017, Beijing, China. Proceedings ICIP 2017 : IEEE International Conference on Image Processing, 2017
Bibtext :
@inproceedings{lopezradcenco:hal-01735256,
TITLE = {{Locally-adapted convolution-based super-resolution of irregularly-sampled ocean remote sensing data}},
AUTHOR = {Lopez Radcenco, Manuel and FABLET, Ronan and A{\"i}ssa-El-Bey, Abdeldjalil and Ailliot, Pierre},
URL = {https://hal.archives-ouvertes.fr/hal-01735256},
BOOKTITLE = {{ICIP 2017 : IEEE International Conference on Image Processing}},
ADDRESS = {Beijing, China},
HAL_LOCAL_REFERENCE = {18018},
PAGES = {.},
YEAR = {2017},
MONTH = Sep,
KEYWORDS = {Super-resolution ; Convolutional model ; Irregular sampling ; Dictionary-based decomposition ; Non-negativity},
PDF = {https://hal.archives-ouvertes.fr/hal-01735256/file/lopez-radcenco_et_al_icip_2017.pdf},
HAL_ID = {hal-01735256},
HAL_VERSION = {v1},
}
Endnote :
%0 Conference Proceedings
%T Locally-adapted convolution-based super-resolution of irregularly-sampled ocean remote sensing data
%+ Lab-STICC_IMTA_CID_TOMS
%+ Département Signal et Communications (SC)
%+ Lab-STICC_IMTA_CACS_COM
%+ Laboratoire de Mathématiques de Bretagne Atlantique (LMBA)
%A Lopez Radcenco, Manuel
%A FABLET, Ronan
%A Aïssa-El-Bey, Abdeldjalil
%A Ailliot, Pierre
%< avec comité de lecture
%Z 18018
%( Proceedings ICIP 2017 : IEEE International Conference on Image Processing
%B ICIP 2017 : IEEE International Conference on Image Processing
%C Beijing, China
%P .
%8 2017-09-17
%D 2017
%K Super-resolution
%K Convolutional model
%K Irregular sampling
%K Dictionary-based decomposition
%K Non-negativity
%Z Statistics [stat]/Machine Learning [stat.ML]Conference papers
%X Super-resolution is a classical problem in image processing, with numerous applications to remote sensing image enhancement. Here, we address the super-resolution of irregularly-sampled remote sensing images. Using an optimal interpolation as the low-resolution reconstruction, we explore locally-adapted multimodal convolutional models and investigate different dictionary-based decompositions, namely based on principal component analysis (PCA), sparse priors and non-negativity constraints. We consider an application to the reconstruction of sea surface height (SSH) fields from two information sources, along-track altimeter data and sea surface temperature (SST) data. The reported experiments demonstrate the relevance of the proposed model, especially locally-adapted parametrizations with non-negativity constraints, to outperform optimally-interpolated reconstructions.
%G English
%2 https://hal.archives-ouvertes.fr/hal-01735256/document
%2 https://hal.archives-ouvertes.fr/hal-01735256/file/lopez-radcenco_et_al_icip_2017.pdf
%L hal-01735256
%U https://hal.archives-ouvertes.fr/hal-01735256
%~ INSTITUT-TELECOM
%~ TELECOM-BRETAGNE
%~ CNRS
%~ UNIV-UBS
%~ MATHBREST
%~ LMBA
%~ ENIB
%~ LAB-STICC
%~ CHL
%~ UNIV-BREST
%~ LAB-STICC_IMTA_CACS_COM
%~ LAB-STICC_IMTA_CID_TOMS
%~ IMTA_SC
%~ IMT-ATLANTIQUE
%~ LAB-STICC_IMTA
Communication dans un congrès
Mai Van Khanh, Pastor Dominique, Aïssa-El-Bey Abdeldjalil, Le Bidan Raphaël
Combined Detection and Estimation Based on Mean-Square Error Log-Spectral Amplitude for Speech Enhancement
GRETSI 2017 : 26ème colloque du Groupement de Recherche en Traitement du Signal et des Images, Sep 2017, Juan-Les-Pins, France. Proceedings GRETSI 2017 : 26ème colloque du Groupement de Recherche en Traitement du Signal et des Images, 2017
Bibtext :
@inproceedings{mai:hal-01611344,
TITLE = {{Combined Detection and Estimation Based on Mean-Square Error Log-Spectral Amplitude for Speech Enhancement}},
AUTHOR = {Mai, Van Khanh and Pastor, Dominique and A{\"i}ssa-El-Bey, Abdeldjalil and Le Bidan, Rapha{\"e}l},
URL = {https://hal.archives-ouvertes.fr/hal-01611344},
BOOKTITLE = {{GRETSI 2017 : 26{\`e}me colloque du Groupement de Recherche en Traitement du Signal et des Images}},
ADDRESS = {Juan-Les-Pins, France},
HAL_LOCAL_REFERENCE = {18209},
PAGES = {.},
YEAR = {2017},
MONTH = Sep,
KEYWORDS = {Speech enhancement},
PDF = {https://hal.archives-ouvertes.fr/hal-01611344/file/mai241.pdf},
HAL_ID = {hal-01611344},
HAL_VERSION = {v1},
}
Endnote :
%0 Conference Proceedings
%T Combined Detection and Estimation Based on Mean-Square Error Log-Spectral Amplitude for Speech Enhancement
%+ Lab-STICC_IMTA_CID_TOMS
%+ Département Signal et Communications (SC)
%+ Lab-STICC_IMTA_CACS_COM
%A Mai, Van Khanh
%A Pastor, Dominique
%A Aïssa-El-Bey, Abdeldjalil
%A Le Bidan, Raphaël
%< avec comité de lecture
%Z 18209
%( Proceedings GRETSI 2017 : 26ème colloque du Groupement de Recherche en Traitement du Signal et des Images
%B GRETSI 2017 : 26ème colloque du Groupement de Recherche en Traitement du Signal et des Images
%C Juan-Les-Pins, France
%P .
%8 2017-09-05
%D 2017
%K Speech enhancement
%Z Engineering Sciences [physics]/Signal and Image processingConference papers
%X In this paper, we address the problem of simultaneously detecting and estimating the speech short-time spectral amplitude (STSA) through combinations of the Neyman-Pearson and Bayesian approaches for speech enhancement. The main idea is that a non-continuous cost function, which depends on the absence/presence of speech, is applied to optimal joint detection and estimation for improving performance of mean square error estimators. Furthermore, our proposed method based on the square error of the logarithmic STSA makes it possible for us to reduce much more the background noise without introducing severe signal distortion. Preliminary experimental results demonstrate the advantage of our method in terms of speech quality and intelligibility
%G English
%2 https://hal.archives-ouvertes.fr/hal-01611344/document
%2 https://hal.archives-ouvertes.fr/hal-01611344/file/mai241.pdf
%L hal-01611344
%U https://hal.archives-ouvertes.fr/hal-01611344
%~ INSTITUT-TELECOM
%~ TELECOM-BRETAGNE
%~ CNRS
%~ UNIV-UBS
%~ ENIB
%~ LAB-STICC
%~ UNIV-BREST
%~ IMTA_SC
%~ LAB-STICC_IMTA_CACS_COM
%~ LAB-STICC_IMTA_CID_TOMS
%~ IMT-ATLANTIQUE
%~ LAB-STICC_IMTA
Communication dans un congrès
Lopez Radcenco Manuel, Aïssa-El-Bey Abdeldjalil, Ailliot Pierre, Fablet Ronan
Décomposition Non-négative de Dynamiques Géophysiques
GRETSI 2017 : 26ème colloque du Groupement de Recherche en Traitement du Signal et des Images, Sep 2017, Juan-Les-Pins, France. Actes GRETSI 2017 : 26ème colloque du Groupement de Recherche en Traitement du Signal et des Images, 2017
Bibtext :
@inproceedings{lopezradcenco:hal-01611337,
TITLE = {{D{\'e}composition Non-n{\'e}gative de Dynamiques G{\'e}ophysiques}},
AUTHOR = {Lopez Radcenco, Manuel and A{\"i}ssa-El-Bey, Abdeldjalil and Ailliot, Pierre and FABLET, Ronan},
URL = {https://hal.archives-ouvertes.fr/hal-01611337},
BOOKTITLE = {{GRETSI 2017 : 26{\`e}me colloque du Groupement de Recherche en Traitement du Signal et des Images}},
ADDRESS = {Juan-Les-Pins, France},
HAL_LOCAL_REFERENCE = {18019},
PAGES = {.},
YEAR = {2017},
MONTH = Sep,
KEYWORDS = {D{\'e}composition non-n{\'e}gative},
HAL_ID = {hal-01611337},
HAL_VERSION = {v1},
}
Endnote :
%0 Conference Proceedings
%T Décomposition Non-négative de Dynamiques Géophysiques
%+ Lab-STICC_IMTA_CID_TOMS
%+ Département Signal et Communications (SC)
%+ Lab-STICC_IMTA_CACS_COM
%+ Laboratoire de Mathématiques de Bretagne Atlantique (LMBA)
%A Lopez Radcenco, Manuel
%A Aïssa-El-Bey, Abdeldjalil
%A Ailliot, Pierre
%A FABLET, Ronan
%< avec comité de lecture
%Z 18019
%( Actes GRETSI 2017 : 26ème colloque du Groupement de Recherche en Traitement du Signal et des Images
%B GRETSI 2017 : 26ème colloque du Groupement de Recherche en Traitement du Signal et des Images
%C Juan-Les-Pins, France
%P .
%8 2017-09-05
%D 2017
%K Décomposition non-négative
%Z Engineering Sciences [physics]/Signal and Image processingConference papers
%X La décomposition des processus géophysiques en modes pertinents est un point clé pour les problèmes de caractérisation, prédiction et reconstruction dans le domaine des sciences de l'environnement. Par ailleurs, la séparation aveugle des contributions associées à différentes sources est un problème classique dans le domaine du traitement de signal et des images. Récemment, des progrès significatifs ont été obtenus avec l'introduction de formulations non-négatives et parcimonieuses. Dans ce travail, nous abordons la décomposition aveugle d'opérateurs linéaires ou de fonctions de transfert entre variables d'intérêt, en mettant l'accent sur un cadre non négatif. Nous illustrons l'intérêt de ces décompositions pour l'analyse, la prédiction et la reconstruction de dynamiques géophysiques.
%G French
%L hal-01611337
%U https://hal.archives-ouvertes.fr/hal-01611337
%~ TELECOM-BRETAGNE
%~ INSTITUT-TELECOM
%~ CNRS
%~ UNIV-UBS
%~ MATHBREST
%~ ENIB
%~ LAB-STICC
%~ CHL
%~ UNIV-BREST
%~ LMBA
%~ IMTA_SC
%~ LAB-STICC_IMTA_CACS_COM
%~ LAB-STICC_IMTA_CID_TOMS
%~ IMT-ATLANTIQUE
%~ LAB-STICC_IMTA
Communication dans un congrès
Lassami Nacerredine, Abed-Meraim Karim, Aïssa-El-Bey Abdeldjalil
Algorithmes de poursuite de sous-espace avec contrainte de parcimonie
GRETSI 2017 : 26ème colloque du Groupement de Recherche en Traitement du Signal et des Images, Sep 2017, Juan-Les-Pins, France. Actes GRETSI 2017 : 26ème colloque du Groupement de Recherche en Traitement du Signal et des Images, 2017
Bibtext :
@inproceedings{lassami:hal-01611336,
TITLE = {{Algorithmes de poursuite de sous-espace avec contrainte de parcimonie}},
AUTHOR = {Lassami, Nacerredine and Abed-Meraim, Karim and A{\"i}ssa-El-Bey, Abdeldjalil},
URL = {https://hal.archives-ouvertes.fr/hal-01611336},
BOOKTITLE = {{GRETSI 2017 : 26{\`e}me colloque du Groupement de Recherche en Traitement du Signal et des Images}},
ADDRESS = {Juan-Les-Pins, France},
HAL_LOCAL_REFERENCE = {18205},
PAGES = {.},
YEAR = {2017},
MONTH = Sep,
KEYWORDS = {Poursuite de sous-espace ; FAPI ; Sparse},
PDF = {https://hal.archives-ouvertes.fr/hal-01611336/file/GRETSI_LASSAMI_rev.pdf},
HAL_ID = {hal-01611336},
HAL_VERSION = {v1},
}
Endnote :
%0 Conference Proceedings
%T Algorithmes de poursuite de sous-espace avec contrainte de parcimonie
%+ 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 Abed-Meraim, Karim
%A Aïssa-El-Bey, Abdeldjalil
%< avec comité de lecture
%Z 18205
%( Actes GRETSI 2017 : 26ème colloque du Groupement de Recherche en Traitement du Signal et des Images
%B GRETSI 2017 : 26ème colloque du Groupement de Recherche en Traitement du Signal et des Images
%C Juan-Les-Pins, France
%P .
%8 2017-09-05
%D 2017
%K Poursuite de sous-espace
%K FAPI
%K Sparse
%Z Engineering Sciences [physics]/Signal and Image processingConference papers
%X Dans cet article, nous considérons la poursuite du sous-espace principal (signal) sous la contrainte de parcimonie de la matrice de poids. Plus précisément, nous proposons une approche en deux étapes où la première utilise l'algorithme FAPI pour une extraction adaptative d'une base orthonormée du sous-espace principal. Une estimation de la matrice de poids souhaitée est effectuée dans la deuxième étape, en tenant compte de la contrainte de parcimonie. Les algorithmes résultants: SS-FAPI et SS-FAPI2 ont une faible complexité de calcul (adaptée au contexte adaptatif) et ils réalisent à la fois de bonnes performances en convergence et en estimation, comme le montrent nos résultats de simulation.
%G French
%2 https://hal.archives-ouvertes.fr/hal-01611336/document
%2 https://hal.archives-ouvertes.fr/hal-01611336/file/GRETSI_LASSAMI_rev.pdf
%L hal-01611336
%U https://hal.archives-ouvertes.fr/hal-01611336
%~ TELECOM-BRETAGNE
%~ INSTITUT-TELECOM
%~ CNRS
%~ UNIV-UBS
%~ MSL
%~ MSL-THESE
%~ ENIB
%~ LAB-STICC
%~ UNIV-BREST
%~ UNIV-ORLEANS
%~ IMTA_SC
%~ LAB-STICC_IMTA_CACS_COM
%~ ENSI-BOURGES
%~ IMT-ATLANTIQUE
%~ LAB-STICC_IMTA
%~ PRISME-CVL
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