Electronique

Nombre total de résultats : 482
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Application des ondelettes à la détermination del’espacement moyen entre diffuseurs

Ahmed Benyahia (2015)
Mémoire de magister

L’espacement moyen entre diffuseurs (MSS) a été identifié comme un paramètre importantpour caractériser les tissus présentant une texture semi-régulière tel que le foie, la rate et lespoumons où le MSS peut être corrélé avec l'état pathologique de ces organes.Notre travail a pour but de déterminer l’espacement moyen entre diffuseurs utilisant lesméthodes de traitement de signal. Plusieurs méthodes exploitants les informations portées par lesspectres d'amplitude des signaux rétrodiffusés des tissus biologiques sont abordées afin d’estimerle MSS: L'autocorrélation fréquentielle (ACF), La méthode Cepstrale, le Cepstre du modèleautorégressif (Cepstre-AR), la densité spectrale de puissance du modèle autorégressif (DSP-AR)et l’autocorrélation fréquentielle du modèle autorégressif (ACF-AR). Une autre méthode récenteest proposée, à savoir : la technique des ondelettes (discrète et continue), nous montrons qu’elleprésente un outil très efficace dans l’extraction du MSS à partir des signaux rétrodiffusés. Lesrésultats de simulations obtenus en utilisant la méthode des ondelettes discrètes sont satisfaisantet plus précis comparativement aux autres méthodes. Voir les détails

Mots clés : échographie, espacement moyen entre diffuseurs, autocorrélation fréquentielle, Cepstre, Transformée en ondelettes, ondelette adaptative à l’écho

Automatic detection of articulations disorders from children’s speech preliminary study

N. Ramou, M. Guerti  (2014)
Publication

Automatic detection of articulations disorders from children’s speech preliminary study Voir les détails

Mots clés : GMM-UBM SVM Model fusion Articulations disorders Speech disorders

Influence of G729 Speech Coding on Automatic Speaker Recognition in VoIP Applications

Dalila Yessad, Abderrahmane Amrouche, Mohamed Debyeche, Naim Ramou  (2012)
Publication

Influence of G729 Speech Coding on Automatic Speaker Recognition in VoIP Applications Voir les détails

Mots clés : Automatic speech recognition (ASR) Universal background model (GMM-UBM) G729 VoIP Resynthesized speech T-norm scoring

Two classifiers score fusion for text independent speaker verification

Ramou, N., Djeddou, M., Guerti, M  (2011)
Publication

Two classifiers score fusion for text independent speaker verification Voir les détails

Mots clés : GMM, SVM

Design and simulation of Pyramidal Horn Antenna for NDT Applications

Z.GUEZOUI, M.amir, H.Amar, M.Zergoug, L.Hamami  (2017)
Publication

This paper describes a pyramidal horn antenna design which it works in a microwave domain. His operating frequency is 4.7 GHz. The parameters of the antenna were measured through its numerical modeling using HFSS (High Frequency Structure Simulator) electromagnetic simulation software. HFSS has the capability to calculate and plot a 3D image depicting the real beam of the gain. The obtained results show that an antenna gain of 12.90 dB was obtained at the frequency of 4.7 GHz, which means that the antenna is properly adapted to the transmission systems. This antenna will be used for non destructive testing (NDT) application, such as detection of cracks in different materials, materials characterization. Voir les détails

Mots clés : Pyramidal horn antenna, Finite Element Method, HFSS, Radiation Pattern, gain, non destructive testing (NDT).

Micrographic Image Segmentation using Level Set Model based on Possibilistic C-Means Clustering

N. Chetih, N. Ramou, Z. Messali, A. SERIR, Y. Boutiche  (2017)
Article de conférence

Image segmentation is often required as a fundamental stage in microstructure material characterization. The objective of this work is to choose hybridization between the Level Set method and the clustering approach in order to extract the characteristics of the materials from the segmentation result of the micrographic images. More specifically, the proposed approach contains two successive necessary stages. The first one consists in the application of possibilistic c-means clustering approach (PCM) to get the various classes of the original image. The second stage is based on using the result of the clustering approach i.e. one class among the three existing classes (which interests us) as an initial contour of the level set method to extract the boundaries of interest region. The main purpose of using the result of the PCM algorithm as initial step of the level set method is to enhance and facilitate the work of the latter. Our experimental results on real micrographic images show that the proposed segmentation method can extract successfully the interest region according to the chosen class and confirm its efficiency for segmenting micrographic images of materials. Voir les détails

Mots clés : Level set, Possibilistic C-Means Clustering, micrographic images, image segmentation.

An Automated Microemboli Detection and Classification System using Backscatter RF Signals and Differential Evolution

Karim FERROUDJI, Nabil Benoudjit, Ayache Bouakaz  (2017)
Publication

Embolic phenomena, whether air or particulate emboli, can induce immediate damages like heart attack or ischemic stroke. Embolus composition (gaseous or particulate matter) is vital in predicting clinically significant complications. Embolus detection using Doppler methods have shown their limits to differentiate solid and gaseous embolus. Radio-Frequency (RF) ultrasound signals backscattered by the emboli contain additional information on the embolus in comparison to the traditionally used Doppler signals. Gaseous bubbles show a nonlinear behavior under specific conditions of the ultrasound excitation wave, this nonlinear behavior is exploited to differentiate solid from gaseous microemboli. In order to verify the usefulness of RF ultrasound signal processing in the detection and classification of microemboli, an in vitro set-up is developed. Sonovue micro bubbles are exploited to mimic the acoustic behavior of gaseous emboli. They are injected at two different concentrations (0.025µl/ml and 0.05µl/ml) in a nonrecirculating flow phantom containing a tube of 0.8 mm in diameter. The tissue mimicking material surrounding the tube is chosen to imitate the acoustic behavior of solid emboli. Both gaseous and solid emboli are imaged using an Anthares ultrasound scanner with a probe emitting at a transmit frequency of 1.82 MHz and at two mechanical indices (MI) 0.2 and 0.6.We propose in this experimental study to exploit discrete wavelet transform (DWT) and a dimensionality reduction algorithm based on differential evolution (DE) technique in the analysis and the characterization of the backscattered RF ultrasound signals from the emboli.Several features are evaluated from the detail coefficients. It should be noted that the features used in this study are the same used in the paper by N. Aydin et al. These all features are used as inputs to the classification models without using feature selection method. Then we perform feature selection using differential evolution algorithm with support vector machines (SVM) classifier. The experimental results show clearly that our proposed method achieves better average classification rates compared to the results obtained in a previous study using also the same backscatter RF signals. Voir les détails

Mots clés : Embolic phenomena, whether air or particulate emboli

Débruitatge De Signal De Bruit De Barkhausenen en Utilisant La Décomposition Des Modes Empirique Pour Optimisation L’évaluation et Caractérisation Des Matériaux

rabah.abdelkader, ZERGOUG Mourad  (2017)
Article de conférence

Dans le domaine contrôle non destructif CND utilise les paramètres électriques et magnétiques des matériaux pour la caractérisation. Parmi ces techniques l’analyse par bruit de Barkhausen, qui est une technique récente développé grâce au progrès de l’électronique. L’information contenue dans le signal reçu offre la possibilité de déterminer plusieurs paramètres dans le but d’analyser le matériau comme toute technique de CND. Le signal de Barkhausen mesuré par l’intermédiaire d’une chaîne de contrôle réalis est noyé par le bruit (bruit blanc) et l'information de l'état des matériaux peut s’être perdue. Nous proposons dans cet article une méthode de débruitage basé sur la décomposition des modes empiriques (EMD) pour optimiser l’utilisation des indicateurs scalaires (kurtosis,RMS) et fréquentielles (FFT, spectre d’enveloppe) de l’évaluation des matériaux. L’EMD décompose d’une façon adaptative un signal en une somme de composantes oscillantes s’appelle les fonctions modales intrinsèques(IMFs) par l’utilisation un processus de tamisage. Après la décomposition on utilise le seuillage doux pour éliminer les IMFs inférieure au seuil . enfin réaliser la reconstruction du signal débruité à l’aide des IMFs débruité. Avec un bon choix du seuil et de l’ondelette utilisée, on arrive à une réduction appréciable du bruit sur le signal de barkhausen et par conséquent une amélioration des indicateurs scalaires. Les résultats obtenus montrent l'intérêt du dé-bruitage pour le contrôle des matériaux par signal de bruit de barkhausen. Voir les détails

Mots clés : bruit de barkhausen, EMD, cnd

Application de l’Algorithme K-S et de l’Ondelette discrète au traitement d’images satellitaires

Rachid AMRAOUI (2015)
Mémoire de magister

This memory approaches the satellite image processing which become a discipline with share today. Its importance is particularly distinguished in case of the forest fires detection, however without doubt; one often faces serious difficulties mainly due to the size of the image, especially when its matrix is treatedin hole. To overcome these constraints, anhybrid line by line treatment method is suggested. The latteris based on the algorithm of Kolmogorov-Smirnov as well as the discrete wavelet, which allows obtaining a lossycompression relative to each line of the matrix.In contrast, the algorithm of Kolmogorov-Smirnov permits to detect the stationary segments for each line. The study aims to combine these two methods in order to get a better representation as optimal as possible of the real image. Voir les détails

Mots clés : each line processing, Discrete-wavelet, KS-algorithm, lossy compression, stationary fragments

Modeling of Electromagnetic Behavior of CompositeThin Layers using Genetic Algorithm

Abdelmalek REDDAF, Karim FERROUDJI, Mounir BOUDJERDA, Khaled Hamdi Chérif, Isslam Bouchachi, fatima Djerfaf  (2017)
Article de conférence

In this paper, we present a new model using the highfrequency electromagnetic simulator for several binary mixtureswhere the load is in the lossless thin film form with a permittivityof (? = 100, 200, 300, and 400) and for various thickness values ina range of 10 µm to 250 µm with respect to the host matrix. Themodel operates in a variety of frequencies from 8.2 GHz to 12.4GHz. The effective permittivity of composites is evaluated usingNicholson Ross Weir (NRW) algorithm in a rectangularwaveguide. The implementation of NRW algorithm is conductedon various samples simulated by HFSS, in order to estimate thedielectric composite behavior. Furthermore, we employ a geneticalgorithm methodology (GA) for the filling factor optimization ofthe proposed model by Mosallaei. The obtained results show agood agreement with the theoretical models, which ensure thevalidity of our proposed model for characterizing theelectromagnetic behaviour of dielectric thin films. Voir les détails

Mots clés : Thin films, electromagnetic behaviour, dielectric mixtures, Genetic optimization, mico wave.