SAM
https://sam.ensam.eu:443
The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.Sat, 13 Apr 2024 17:28:53 GMT2024-04-13T17:28:53ZOn signals compression by EMD
http://hdl.handle.net/10985/8856
On signals compression by EMD; Codage des signaux par EMD
KHALDI, Kais; BOUDRAA, Abdel-Ouahab
In this letter a new signals coding framework based on the Empirical Mode Decomposition (EMD) is introduced. The EMD breaks down any signal into a reduced number of oscillating components called Intrinsic Modes Decomposition (IMFs). Based on IMF properties, different coding strategies are presented. No assumptions concerning the linearity or the stationarity are made about the signal to be coded. Results obtained on ECG signals are presented and compared to those of wavelets coding.
Sun, 01 Jan 2012 00:00:00 GMThttp://hdl.handle.net/10985/88562012-01-01T00:00:00ZKHALDI, KaisBOUDRAA, Abdel-OuahabIn this letter a new signals coding framework based on the Empirical Mode Decomposition (EMD) is introduced. The EMD breaks down any signal into a reduced number of oscillating components called Intrinsic Modes Decomposition (IMFs). Based on IMF properties, different coding strategies are presented. No assumptions concerning the linearity or the stationarity are made about the signal to be coded. Results obtained on ECG signals are presented and compared to those of wavelets coding.Passive stochastic matched filter for Antarctic blue whale call detection
http://hdl.handle.net/10985/15081
Passive stochastic matched filter for Antarctic blue whale call detection
BOUFFAUT, Léa; DRÉO, Richard; LABAT, Valérie; BOUDRAA, Abdel-Ouahab; BARRUOL, Guilhem
As a first step to Antarctic blue whale (ABW) monitoring using passive acoustics, a method based on the stochastic matched filter (SMF) is proposed. Derived from the matched filter (MF), this filter-based denoising method enhances stochastic signals embedded in an additive colored noise by maximizing its output signal to noise ratio (SNR). These assumptions are well adapted to the passive detection of ABW calls where emitted signals are modified by the unknown impulse response of the propagation channel. A filter bank is computed and stored offline based on a priori knowledge of the signal second order statistics and simulated colored sea-noise. Then, the detection relies on online background noise and SNR estimation, realized using time-frequency analysis. The SMF output is cross-correlated with the signal’s reference (SMF þ MF). Its performances are assessed on an ccean bottom seismometer-recorded ground truth dataset of 845 ABW calls, where the location of the whale is known. This dataset provides great SNR variations in diverse soundscapes. The SMF þ MF performances are compared to the commonly used MF and to the Z-detector (a subspace detector for ABW calls). Mostly, the benefits of the use of the SMF þ MF are revealed on low signal to noise observations: in comparison to the MF with identical detection threshold, the false alarm rate drastically decreases while the detection rate stays high. Compared to the Z-detector, it allows the extension of the detection range of ’ 30 km in presence of ship noise with equivalent false discovery rate.
Mon, 01 Jan 2018 00:00:00 GMThttp://hdl.handle.net/10985/150812018-01-01T00:00:00ZBOUFFAUT, LéaDRÉO, RichardLABAT, ValérieBOUDRAA, Abdel-OuahabBARRUOL, GuilhemAs a first step to Antarctic blue whale (ABW) monitoring using passive acoustics, a method based on the stochastic matched filter (SMF) is proposed. Derived from the matched filter (MF), this filter-based denoising method enhances stochastic signals embedded in an additive colored noise by maximizing its output signal to noise ratio (SNR). These assumptions are well adapted to the passive detection of ABW calls where emitted signals are modified by the unknown impulse response of the propagation channel. A filter bank is computed and stored offline based on a priori knowledge of the signal second order statistics and simulated colored sea-noise. Then, the detection relies on online background noise and SNR estimation, realized using time-frequency analysis. The SMF output is cross-correlated with the signal’s reference (SMF þ MF). Its performances are assessed on an ccean bottom seismometer-recorded ground truth dataset of 845 ABW calls, where the location of the whale is known. This dataset provides great SNR variations in diverse soundscapes. The SMF þ MF performances are compared to the commonly used MF and to the Z-detector (a subspace detector for ABW calls). Mostly, the benefits of the use of the SMF þ MF are revealed on low signal to noise observations: in comparison to the MF with identical detection threshold, the false alarm rate drastically decreases while the detection rate stays high. Compared to the Z-detector, it allows the extension of the detection range of ’ 30 km in presence of ship noise with equivalent false discovery rate.Antarctic Blue Whale Calls Detection Based on an Improved Version of the Stochastic Matched Filter
http://hdl.handle.net/10985/15083
Antarctic Blue Whale Calls Detection Based on an Improved Version of the Stochastic Matched Filter
BOUFFAUT, Léa; DREO, Richard; LABAT, Valérie; BOUDRAA, Abdel-Ouahab; BARRUOL, Guilhem
As a first step to Antarctic Blue Whale monitoring, a new method based on a passive application of the Stochastic Matched Filter (SMF) is developed. To perform Z-call detection in noisy environment, improvements on the classical SMF requirements are proposed. The signal’s reference is adjusted, the background noise estimation is reevaluated to avoid operator’s selection, and the time-dependent Signal to Noise Ratio (SNR) estimation is revised by time-frequency analysis. To highlight the SMF’s robustness against noise, it is applied on a Ocean Bottom Seismometers hydrophone-recorded data and compared to the classical Matched Filter: the output’s SNR is maximized and the false alarm drastically decreased.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/150832017-01-01T00:00:00ZBOUFFAUT, LéaDREO, RichardLABAT, ValérieBOUDRAA, Abdel-OuahabBARRUOL, GuilhemAs a first step to Antarctic Blue Whale monitoring, a new method based on a passive application of the Stochastic Matched Filter (SMF) is developed. To perform Z-call detection in noisy environment, improvements on the classical SMF requirements are proposed. The signal’s reference is adjusted, the background noise estimation is reevaluated to avoid operator’s selection, and the time-dependent Signal to Noise Ratio (SNR) estimation is revised by time-frequency analysis. To highlight the SMF’s robustness against noise, it is applied on a Ocean Bottom Seismometers hydrophone-recorded data and compared to the classical Matched Filter: the output’s SNR is maximized and the false alarm drastically decreased.Antartic blue whale localization with ocean bottom seismometers in southern indian ocean
http://hdl.handle.net/10985/15086
Antartic blue whale localization with ocean bottom seismometers in southern indian ocean
DREO, Richard; BOUFFAUT, Léa; GUILLON, Laurent; LABAT, Valérie; BARRUOL, Guilhem; BOUDRAA, Abdel-Ouahab
While visual survey of whales requires substantial means for limited areas, passive acoustic monitoring (PAM) offers larger scale coverage for long periods and less costs. It usually provides information about species behavior, e.g. seasonal movements, but tools are needed to detail the individuals' behavior. From October 2012 to November 2013 as part of the German-French "RHUM-RUM" (Réunion Hotspot and Upper Mantle - Réunion Unterer Mantel) seismic experiment, a 70km by 40km array of 8 Ocean Bottom Seismometers (OBS) was deployed in Southern Indian Ocean in a mountainous area, with depths from 2500 to 5500 meters. The [0-50] Hz-frequency band covered by the OBS's hydrophone provides observations about whales. Each source-OBS path has its own acoustic propagation. Indeed, closest OBS can be reached by direct rays, while remote OBS can only be reached by multi-reflected rays. Therefore, the localization problem cannot be solved directly using a classical Time Difference Of Arrival (TDOA) algorithm. In this work, the TDOA problem is solved in the case of long range detection, even with mountainous relief, enabling localization and tracking of whales. For each point of the spatial matrix representing the area, Times Of Arrival (TOA) of signal on the OBS are computed with a ray tracing algorithm (BELLHOP), taking into account the bottom profile. The theoretical corresponding TDOA are then compared to measured ones using a loss function. The obtained results, using L1, L2, cross-correlation cost functions, show the effectiveness of the proposed strategy to track whales on their calls. For example, an Antarctic blue whale is tracked during 10 hours from 40 kilometers south of the array center to 40 kilometers north where the mean speed is close to 10 km/h on a straight trajectory.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/150862017-01-01T00:00:00ZDREO, RichardBOUFFAUT, LéaGUILLON, LaurentLABAT, ValérieBARRUOL, GuilhemBOUDRAA, Abdel-OuahabWhile visual survey of whales requires substantial means for limited areas, passive acoustic monitoring (PAM) offers larger scale coverage for long periods and less costs. It usually provides information about species behavior, e.g. seasonal movements, but tools are needed to detail the individuals' behavior. From October 2012 to November 2013 as part of the German-French "RHUM-RUM" (Réunion Hotspot and Upper Mantle - Réunion Unterer Mantel) seismic experiment, a 70km by 40km array of 8 Ocean Bottom Seismometers (OBS) was deployed in Southern Indian Ocean in a mountainous area, with depths from 2500 to 5500 meters. The [0-50] Hz-frequency band covered by the OBS's hydrophone provides observations about whales. Each source-OBS path has its own acoustic propagation. Indeed, closest OBS can be reached by direct rays, while remote OBS can only be reached by multi-reflected rays. Therefore, the localization problem cannot be solved directly using a classical Time Difference Of Arrival (TDOA) algorithm. In this work, the TDOA problem is solved in the case of long range detection, even with mountainous relief, enabling localization and tracking of whales. For each point of the spatial matrix representing the area, Times Of Arrival (TOA) of signal on the OBS are computed with a ray tracing algorithm (BELLHOP), taking into account the bottom profile. The theoretical corresponding TDOA are then compared to measured ones using a loss function. The obtained results, using L1, L2, cross-correlation cost functions, show the effectiveness of the proposed strategy to track whales on their calls. For example, an Antarctic blue whale is tracked during 10 hours from 40 kilometers south of the array center to 40 kilometers north where the mean speed is close to 10 km/h on a straight trajectory.Filtrage Adapté Stochastique passif pour la détection de plongeurs
http://hdl.handle.net/10985/15140
Filtrage Adapté Stochastique passif pour la détection de plongeurs
BOUFFAUT, Léa; DREO, Richard; LABAT, Valérie; BOUDRAA, Abdel-Ouahab
De par sa discrétion, la détection passive est un atout majeur pour la surveillance de zones maritimes, notamment dans le cas de détection de plongeurs intrus dans les zones portuaires. Des outils de traitement du signal adaptés au contexte passif sont nécessaires afin de minimiser le temps de réaction des opérateurs, voire même d’automatiser le processus. En pratique, les méthodes basées sur la démodulation d’amplitude ou DEMON (DEModulation Of Noise) sont les plus utilisées, mais atteignent leurs limitations pour la détection de sources à faible Rapport Signal sur Bruit (RSB) (bateaux, plongeurs, AUV...). Une stratégie pour maximiser le RSB est le Filtrage Adapté Stochastique (FAS), que nous étendons dans ce travail au contexte passif. La contribution majeure, réside dans l’étape cruciale de l’estimation du bruit de fond qui ne nécessite plus d’information a priori sur la répartition du bruit dans l’observation. Cette nouvelle méthode est alors appliquée sur un enregistrement de cycles respiratoires de deux plongeurs en piscine. Les résultats montrent qu’il est possible d’adapter les hypothèses du FAS au contexte passif pour maximiser le RSB en sortie de processus, permettant ainsi d’optimiser la détection.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/151402017-01-01T00:00:00ZBOUFFAUT, LéaDREO, RichardLABAT, ValérieBOUDRAA, Abdel-OuahabDe par sa discrétion, la détection passive est un atout majeur pour la surveillance de zones maritimes, notamment dans le cas de détection de plongeurs intrus dans les zones portuaires. Des outils de traitement du signal adaptés au contexte passif sont nécessaires afin de minimiser le temps de réaction des opérateurs, voire même d’automatiser le processus. En pratique, les méthodes basées sur la démodulation d’amplitude ou DEMON (DEModulation Of Noise) sont les plus utilisées, mais atteignent leurs limitations pour la détection de sources à faible Rapport Signal sur Bruit (RSB) (bateaux, plongeurs, AUV...). Une stratégie pour maximiser le RSB est le Filtrage Adapté Stochastique (FAS), que nous étendons dans ce travail au contexte passif. La contribution majeure, réside dans l’étape cruciale de l’estimation du bruit de fond qui ne nécessite plus d’information a priori sur la répartition du bruit dans l’observation. Cette nouvelle méthode est alors appliquée sur un enregistrement de cycles respiratoires de deux plongeurs en piscine. Les résultats montrent qu’il est possible d’adapter les hypothèses du FAS au contexte passif pour maximiser le RSB en sortie de processus, permettant ainsi d’optimiser la détection.A New class of multi-dimensional Teager Kaiser and higher order operators based on directional derivatives
http://hdl.handle.net/10985/8857
A New class of multi-dimensional Teager Kaiser and higher order operators based on directional derivatives; Une nouvelle classe d'opérateurs de Teager-Kaiser multidimensionnels basée sur les dérivées directionnelles d'ordre supérieur
SALZENSTEIN, Fabien; BOUDRAA, Abdel-Ouahab; CHONAVEL, Thierry
This work aims at introducing some energy operators linked to Teager-Kaiser energy operator and its associated higher order versions and expand them to multidimensional signals. These operators are very useful for analyzing oscillatory signals with time-varying amplitude and frequency (AM-FM). We prove that gradient tensors combined with Kronecker powers allow to express these operators by directional derivatives along any n-D vector. In particular, we show that the construction of a large class of non linear operators for AM-FM multidimensional signal demodulation is possible. Also, a new scalar function using the directional derivative along a vector giving the ”sign” of the frequency components is introduced. An application of this model to local n-D AM-FM signal is presented and related demodulation error rates estimates. To show the effectiveness and the robustness of our method in term of envelope and frequency components extraction, results obtained on synthetic and real data are compared to multi-dimensional energy separation algorithm and to our recently introduced n-D operator.
Tue, 01 Jan 2013 00:00:00 GMThttp://hdl.handle.net/10985/88572013-01-01T00:00:00ZSALZENSTEIN, FabienBOUDRAA, Abdel-OuahabCHONAVEL, ThierryThis work aims at introducing some energy operators linked to Teager-Kaiser energy operator and its associated higher order versions and expand them to multidimensional signals. These operators are very useful for analyzing oscillatory signals with time-varying amplitude and frequency (AM-FM). We prove that gradient tensors combined with Kronecker powers allow to express these operators by directional derivatives along any n-D vector. In particular, we show that the construction of a large class of non linear operators for AM-FM multidimensional signal demodulation is possible. Also, a new scalar function using the directional derivative along a vector giving the ”sign” of the frequency components is introduced. An application of this model to local n-D AM-FM signal is presented and related demodulation error rates estimates. To show the effectiveness and the robustness of our method in term of envelope and frequency components extraction, results obtained on synthetic and real data are compared to multi-dimensional energy separation algorithm and to our recently introduced n-D operator.Multicomponent AM-FM signals analysis based on EMD-B-splines ESA
http://hdl.handle.net/10985/9053
Multicomponent AM-FM signals analysis based on EMD-B-splines ESA; Analyse des signaux AM-FM basée sur une version B-splines de l'EMD-ESA
BOUCHIKHI, Abdelkhalek; BOUDRAA, Abdel-Ouahab
In this paper a signal analysis framework for estimating time-varying amplitude and frequency functions of multicomponent amplitude and frequency modulated (AM–FM) signals is introduced. This framework is based on local and non-linear approaches, namely Energy Separation Algorithm (ESA) and Empirical Mode Decomposition (EMD). Conjunction of Discrete ESA (DESA) and EMD is called EMD–DESA. A new modified version of EMD where smoothing instead of an interpolation to construct the upper and lower envelopes of the signal is introduced. Since extracted IMFs are represented in terms of B-spline (BS) expansions, a closed formula of ESA robust against noise is used. Instantaneous Frequency (IF) and Instantaneous Amplitude (IA) estimates of a multi- component AM–FM signal, corrupted with additive white Gaussian noise of varying SNRs, are analyzed and results compared to ESA, DESA and Hilbert transform-based algorithms. SNR and MSE are used as figures of merit. Regularized BS version of EMD– ESA performs reasonably better in separating IA and IF components compared to the other methods from low to high SNR. Overall, obtained results illustrate the effective- ness of the proposed approach in terms of accuracy and robustness against noise to track IF and IA features of a multicomponent AM–FM signal.
Sun, 01 Jan 2012 00:00:00 GMThttp://hdl.handle.net/10985/90532012-01-01T00:00:00ZBOUCHIKHI, AbdelkhalekBOUDRAA, Abdel-OuahabIn this paper a signal analysis framework for estimating time-varying amplitude and frequency functions of multicomponent amplitude and frequency modulated (AM–FM) signals is introduced. This framework is based on local and non-linear approaches, namely Energy Separation Algorithm (ESA) and Empirical Mode Decomposition (EMD). Conjunction of Discrete ESA (DESA) and EMD is called EMD–DESA. A new modified version of EMD where smoothing instead of an interpolation to construct the upper and lower envelopes of the signal is introduced. Since extracted IMFs are represented in terms of B-spline (BS) expansions, a closed formula of ESA robust against noise is used. Instantaneous Frequency (IF) and Instantaneous Amplitude (IA) estimates of a multi- component AM–FM signal, corrupted with additive white Gaussian noise of varying SNRs, are analyzed and results compared to ESA, DESA and Hilbert transform-based algorithms. SNR and MSE are used as figures of merit. Regularized BS version of EMD– ESA performs reasonably better in separating IA and IF components compared to the other methods from low to high SNR. Overall, obtained results illustrate the effective- ness of the proposed approach in terms of accuracy and robustness against noise to track IF and IA features of a multicomponent AM–FM signal.Instantaneous frequency estimation of FM signals by Psi_B-energy operator
http://hdl.handle.net/10985/8859
Instantaneous frequency estimation of FM signals by Psi_B-energy operator; Estimation de la fréquence instantanée des signaux FM par opérateur d'énergie Psi_B
BOUDRAA, Abdel-Ouahab
Psi_B energy operator is an extension of the cross Teager-Kaiser energy operator which is an non-linear energy tracking operator to deal with complex signals and its usefulness for non-stationary signals analysis has been demonstrated. In this letter two new properties of Psi_B are established. The first property is the link between Psi_B and the dynamic signal which is a generalization of the Instantaneous Frequency (IF). The second property obtained for frequency modulated signals is a simple way to estimate the IF. These properties confirm the interest of Psi_B operator to track the non-stationary of a signal. Results of IF estimation in noisy environment of a non-linear FM signal are presented and comparison to Wigner-Ville distribution and Hilbert transform-based method is provided.
Sat, 01 Jan 2011 00:00:00 GMThttp://hdl.handle.net/10985/88592011-01-01T00:00:00ZBOUDRAA, Abdel-OuahabPsi_B energy operator is an extension of the cross Teager-Kaiser energy operator which is an non-linear energy tracking operator to deal with complex signals and its usefulness for non-stationary signals analysis has been demonstrated. In this letter two new properties of Psi_B are established. The first property is the link between Psi_B and the dynamic signal which is a generalization of the Instantaneous Frequency (IF). The second property obtained for frequency modulated signals is a simple way to estimate the IF. These properties confirm the interest of Psi_B operator to track the non-stationary of a signal. Results of IF estimation in noisy environment of a non-linear FM signal are presented and comparison to Wigner-Ville distribution and Hilbert transform-based method is provided.Estimation des paramètres d'un processus Symétrique Alpha Stable (S-alpha-Stable) à partir de ses modes empiriques
http://hdl.handle.net/10985/10092
Estimation des paramètres d'un processus Symétrique Alpha Stable (S-alpha-Stable) à partir de ses modes empiriques
KOMATY, Ali; BOUDRAA, Abdel-Ouahab; DARE-EMZIVAT, Delphine
Dans ce travail nous nous intéressons au problème d’estimation des paramètres d’un processus alpha stable symétrique à partir de ses modes empiriques extraits par la décomposition modale empirique multivariée (MEMD). Nous exploitons le fait que le caractère impulsif du bruit est mieux préservé par ses premiers modes empiriques pour estimer son exposant caractéristique ainsi que son facteur d’échelle. Nous montrons que les paramètres du processus sont mieux estimés à partir de ses modes empiriques que du processus lui-même. Des résultats d’estimation des paramères utilisant le MEMD sont présentés et comparés à ceux des estimateurs basés sur les quantiles et la fonction caractéristique empirique.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/100922015-01-01T00:00:00ZKOMATY, AliBOUDRAA, Abdel-OuahabDARE-EMZIVAT, DelphineDans ce travail nous nous intéressons au problème d’estimation des paramètres d’un processus alpha stable symétrique à partir de ses modes empiriques extraits par la décomposition modale empirique multivariée (MEMD). Nous exploitons le fait que le caractère impulsif du bruit est mieux préservé par ses premiers modes empiriques pour estimer son exposant caractéristique ainsi que son facteur d’échelle. Nous montrons que les paramètres du processus sont mieux estimés à partir de ses modes empiriques que du processus lui-même. Des résultats d’estimation des paramères utilisant le MEMD sont présentés et comparés à ceux des estimateurs basés sur les quantiles et la fonction caractéristique empirique.Analyse de la vulnérabilité d’un réseau via la mesure de l’entropie de Von Neumann.
http://hdl.handle.net/10985/23425
Analyse de la vulnérabilité d’un réseau via la mesure de l’entropie de Von Neumann.
BAY-AHMED, Hadj-Ahmed; DARE-EMZIVAT, Delphine; BOUDRAA, Abdel-Ouahab
In this work, we present a new strategy for measuring the vulnerability of network connections, modeled by a graph, via the
variations of the Von Neumann entropy of the density matrix associated to this graph, this one being seen as a quantum system. We show that the change of the weight of an edge impacts the resulting Von Neumann entropy, which includes not only the intensity of the perturbation induced but also a quantity related to the degrees of the nodes adjacent to the perturbed edge. An algorithm based on this strategy has been developed. The obtained results confirm the relevance of this new measure. Our algorithm highlights the discontinuities that could appear in the structure by proposing a hierarchical decomposition into subgraphs relative to the degrees of vulnerability of the edges. The obtained map guarantees a better network security.
Sun, 01 Sep 2019 00:00:00 GMThttp://hdl.handle.net/10985/234252019-09-01T00:00:00ZBAY-AHMED, Hadj-AhmedDARE-EMZIVAT, DelphineBOUDRAA, Abdel-OuahabIn this work, we present a new strategy for measuring the vulnerability of network connections, modeled by a graph, via the
variations of the Von Neumann entropy of the density matrix associated to this graph, this one being seen as a quantum system. We show that the change of the weight of an edge impacts the resulting Von Neumann entropy, which includes not only the intensity of the perturbation induced but also a quantity related to the degrees of the nodes adjacent to the perturbed edge. An algorithm based on this strategy has been developed. The obtained results confirm the relevance of this new measure. Our algorithm highlights the discontinuities that could appear in the structure by proposing a hierarchical decomposition into subgraphs relative to the degrees of vulnerability of the edges. The obtained map guarantees a better network security.