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Mounir Samet

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Papers by Mounir Samet

Behavioral modeling and simulation of underwater channel

WSEAS TRANSACTIONS on COMMUNICATIONS archive, Feb 1, 2009

The Ocean is a dynamic and complex environment; it is a very complicated transmission channel tha... more The Ocean is a dynamic and complex environment; it is a very complicated transmission channel that can change rapidly with the environmental conditions. Hence, to avoid failure of underwater monitoring missions, it's crucial to predict the behavior of underwater acoustic channel. In this paper, several fundamental key aspects of underwater acoustic channel are investigated. A model characterizing the underwater acoustic channel is introduced, and how underwater channel can be simulated is discussed. In addition, this paper describes a methodology for top-down design, modeling, and simulation of underwater channel using hardware description language VHDL-AMS. The following analysis may provide precious guidelines for the design of underwater communication systems.

Low power consumption , low phase noise ring oscillator in 0 . 18 μm CMOS process

In this work, a new ring voltage controlled oscillator with a two cross coupled load PMOS transis... more In this work, a new ring voltage controlled oscillator with a two cross coupled load PMOS transistors is proposed. The proposed method preserves the maximum frequency of the VCO unaffected which leads to improvement in phase noise and the power consumption of VCO oscillators. The proposed ring oscillator implemented in 0.18μm CMOS shows the worse phase noise of -108 dBc/Hz at 10MHz offset, tuning range of 140.7%, while dissipating a maximum power consumption of 9 mW from 1.8 V supply. Keywords— Ring oscillators, VCO, tuning range, phase noise, cross coupled PMOS transistors.

– TUNISIA-1-Design and Optimization of a Voltage Controlled Oscillator for RFID System

This paper devote with a method of optimization of phase noise used to design a 0.35μm CMOS fully... more This paper devote with a method of optimization of phase noise used to design a 0.35μm CMOS fully integrated LC voltage controlled oscillator, suitab le for Radio Frequency Identification (RFID) reader working at 2.4 GHz. This method allowed finding the optimal VCO di mensions which give a best phase noise performance by visualizing the design constraints such as power di ssipation, tank amplitude, frequency tuning range a nd start-up condition graphically. The results phase noise is -126 dBc/Hz at 1MHz offs et rom a 2.4 GHz carrier. The designed VCO dissipa tes 5mA from a 2.5V supply voltage. Key-Words: RFID, Voltage Controlled Oscillator, Phase noise INTRODUCTION In recent years, there has been growing interest in the development of the Radio frequency identificati on (RFID). RFID system is a wireless communication system in which the radio link between the reader a nd the tag are furnished by the modulated back-scatter ed waves [RAO 99]. To realize backscattered RFID system, one ...

Approche Multi Automatique des Mots Isolés et Phonèmes Arabes

Resumé : Cet article concerne l’introduction d’un modèle parallèle pour la reconnaissance automat... more Resumé : Cet article concerne l’introduction d’un modèle parallèle pour la reconnaissance automatique de Arabe (mots isolés et phonèmes) puisque l’arabe est la cinquième langue parlée dans le monde avec un nombre estimé de 300 millions de locuteurs. Le choix d’une telle approche réside dans l’hypothèse que des reconnaisseurs travaillant indépendamment sur différents sousensembles de paramètres acoustiques sont plus robustes qu’un seul reconnaisseur utilisant l’espace acoustique dans sa globalité. Cet approche, dite multi améliorer la performance d'un systèm résolution de la transformée en ondelettes (ou Discret Wavelet Transform DWT), le son articulé d'entrée est décomposé en diverses bandes de fréquence. Pour capturer les caractéristiq linéaires cepstraux (LPCCs) de chaque bande sont calculés. Nous allons considérer lors de l’étude de cette approche multi-bandes une modélisation Markovienne (HMM). La combinaison du système multibande taux de reconnaissance par rapport aux d...

Meet Spinky: An Open-Source Spindle and K-Complex Detection Toolbox Validated on the Open-Access Montreal Archive of Sleep Studies (MASS)

Frontiers in neuroinformatics, 2017

Sleep spindles and K-complexes are among the most prominent micro-events observed in electroencep... more Sleep spindles and K-complexes are among the most prominent micro-events observed in electroencephalographic (EEG) recordings during sleep. These EEG microstructures are thought to be hallmarks of sleep-related cognitive processes. Although tedious and time-consuming, their identification and quantification is important for sleep studies in both healthy subjects and patients with sleep disorders. Therefore, procedures for automatic detection of spindles and K-complexes could provide valuable assistance to researchers and clinicians in the field. Recently, we proposed a framework for joint spindle and K-complex detection (Lajnef et al., 2015a) based on a Tunable Q-factor Wavelet Transform (TQWT; Selesnick, 2011a) and morphological component analysis (MCA). Using a wide range of performance metrics, the present article provides critical validation and benchmarking of the proposed approach by applying it to open-access EEG data from the Montreal Archive of Sleep Studies (MASS; O'Re...

Sleep spindle and K-complex detection using tunable Q-factor wavelet transform and morphological component analysis

Frontiers in human neuroscience, 2015

A novel framework for joint detection of sleep spindles and K-complex events, two hallmarks of sl... more A novel framework for joint detection of sleep spindles and K-complex events, two hallmarks of sleep stage S2, is proposed. Sleep electroencephalography (EEG) signals are split into oscillatory (spindles) and transient (K-complex) components. This decomposition is conveniently achieved by applying morphological component analysis (MCA) to a sparse representation of EEG segments obtained by the recently introduced discrete tunable Q-factor wavelet transform (TQWT). Tuning the Q-factor provides a convenient and elegant tool to naturally decompose the signal into an oscillatory and a transient component. The actual detection step relies on thresholding (i) the transient component to reveal K-complexes and (ii) the time-frequency representation of the oscillatory component to identify sleep spindles. Optimal thresholds are derived from ROC-like curves (sensitivity vs. FDR) on training sets and the performance of the method is assessed on test data sets. We assessed the performance of ou...

A Robustness Comparison of Two Algorithms Used for EEG Spike Detection

The Open Biomedical Engineering Journal, 2015

Spikes and sharp waves recorded on scalp EEG may play an important role in identifying the epilep... more Spikes and sharp waves recorded on scalp EEG may play an important role in identifying the epileptogenic network as well as in understanding the central nervous system. Therefore, several automatic and semi-automatic methods have been implemented to detect these two neural transients. A consistent gold standard associated with a high degree of agreement among neuroscientists is required to measure relevant performance of different methods. In fact, scalp EEG data can often be corrupted by a set of artifacts and are not always served as data of gold standard. For this reason, the use of intracerebral EEG data mixed with gaussian noise seems to best resemble the output of scalp EEG brain and serves as a consistent gold standard. In the present framework, we test the robustness of two important methods that have been previously used for the automatic detection of epileptiform transients (spikes and sharp waves). These methods are based respectively on Discrete Wavelet Transform (DWT) a...

Analysis Study Of Time Synchronization Protocols In Wireless Sensor Networks

International Journal of Distributed and Parallel systems, 2012

One of the main pervasive problems Wireless Sensor Networks (WSN) encounter is to maintain flawle... more One of the main pervasive problems Wireless Sensor Networks (WSN) encounter is to maintain flawless communication sharing and cooperative processing between sensors via radio links to ensure a reliable treatment of information. Many applications based on these WSNs consider local clocks at each sensor node that need to be synchronized to a common notion of time. In this context, the majority of previous researches were focused on the study of protocols, and algorithms that address these issues in order to resolve synchronization problems. Previous fforts and empirical studies in wireless sensor network (WSN) proposed several solutions (algorithms). The focus of this this paper is to examine and evaluate the most important synchronization algorithms based on the positions of various quantitative and qualitative synchronization protocols for energy-efficient information processing and routing in WSNs.

Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines

Journal of Neuroscience Methods, 2015

Background: Sleep staging is a critical step in a range of electrophysiological signal processing... more Background: Sleep staging is a critical step in a range of electrophysiological signal processing pipelines used in clinical routine as well as in sleep research. Although the results currently achievable with automatic sleep staging methods are promising, there is need for improvement, especially given the time-consuming and tedious nature of visual sleep scoring. New method: Here we propose a sleep staging framework that consists of a multi-class support vector machine (SVM) classification based on a decision tree approach. The performance of the method was evaluated using polysomnographic data from 15 subjects (electroencephalogram (EEG), electrooculogram (EOG) and electromyogram (EMG) recordings). The decision tree, or dendrogram, was obtained using a hierarchical clustering technique and a wide range of time and frequency-domain features were extracted. Feature selection was carried out using forward sequential selection and classification was evaluated using k-fold cross-validation. Results: The dendrogram-based SVM (DSVM) achieved mean specificity, sensitivity and overall accuracy of 0.92, 0.74 and 0.88 respectively, compared to expert visual scoring. Restricting DSVM classification to data where both experts' scoring was consistent (76.73% of the data) led to a mean specificity, sensitivity and overall accuracy of 0.94, 0.82 and 0.92 respectively. Comparison with existing methods: The DSVM framework outperforms classification with more standard multi-class "one-against-all" SVM and linear-discriminant analysis. Conclusion: The promising results of the proposed methodology suggest that it may be a valuable alternative to existing automatic methods and that it could accelerate visual scoring by providing a robust starting hypnogram that can be further fine-tuned by expert inspection.

Crypto-compression of images based on chaos

2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), 2012

ABSTRACT

Modulation/demodulation techniques with FPGA's architecture to improve OFDM wireless underwater communication transceiver

International Conference on Design and Test of Integrated Systems in Nanoscale Technology, 2006. DTIS 2006., 2006

In order to improve the efficiency multi band OFDM wireless underwater communication, the softwar... more In order to improve the efficiency multi band OFDM wireless underwater communication, the software technology offers the ability to develop OFDM transceiver architecture and his performance by using an optimal modulation and coding schema. The field programmable gate array (FPGA) represents a solution to have flexible mapping that adjusts several types of modulation. This paper aims to specify a new

The pilot-induced cyclostationarity approach for the OFDM WIFI identification

Eighth International Multi-Conference on Systems, Signals & Devices, 2011

This paper presents an approach that enables the receiver to identify the DVB standard among diff... more This paper presents an approach that enables the receiver to identify the DVB standard among different systems employing the OFDM technique (Orthogonal Frequency Division Multiplexing) consisting of large number of mutually orthogonal sub carriers. This characteristic provides high robustness against multi-path effects. The pilot induced cyclostationarity (PIC) approach is one of the new algorithms introduced recently to discuss the OFDM systems identification problem. Although this algorithm reflects good performance in term of correct classification, it still suffers from some limitations when identifying some standard such as DVB. In this paper, we are looking for the DVB recognition based on the PIC. Simulation results show that system recognition based on the proposed method exhibits excellent correct detection probability.

Efficient and secure chaotic S-Box for wireless sensor network

Security and Communication Networks, 2013

OATAO is an open access repository that collects the work of Toulouse researchers and makes it fr... more

Electronic and Mac Protocol Characterization of RFID Modules

Radio Frequency Identification Fundamentals and Applications Bringing Research to Practice, 2010

Feature extraction by wavelet transforms to analyze the heart rate variability during two meditation techniques

Lecture Notes in Electrical Engineering, 2009

In this study we present the analysis of HRV signals by wavelet transform. HRV, described by the ... more In this study we present the analysis of HRV signals by wavelet transform. HRV, described by the extraction of the physiological rhythms embedded within its signal, is the tool through which adaptations of activity of the ANS have been widely studied. The assessment of wavelet transform (WT) as a feature extraction method was used in representing the electrophysiological signals. The purpose of all this is to study the ANS system of subjects who are doing some meditation exercises such as the Chi and Yoga. The computed detail wavelet coefficients of the HRV signals were used as the feature vectors representing the signals. These parameters characterize the behavior of the ANS. In order to reduce the dimensionality of the data under study, the following statistical parameters were computed.

A Beta basis function neural network in CMOS subthreshold mode

International Journal of Electronics, 2001

Beta basis function neural networks (BBFNNs) are powerful systems for learning and universal appr... more

Automated detection and classification of high frequency oscillations (HFOs) in human intracereberal EEG

Biomedical Signal Processing and Control, 2013

High Frequency Oscillations (HFOs) in the range of 80-500Hz seem to be a reliable bio marker of t... more High Frequency Oscillations (HFOs) in the range of 80-500Hz seem to be a reliable bio marker of tissue capable of producing seizures. Visual marking of HFOs related to long duration/multi channel EEG data is extremely tedious, highly time-consuming and inevitably subjective. Therefore, automated and reliable detection of HFOs is much more efficient. The purpose of the present study is to improve in the first stage three existing HFOs detectors (CM V, MP, BMT), and subsequently compare them on the same database. Our main findings are summa rized as follows: The efficiency of methods depends on the required sensitivity and the False Discovery Rate (FDR). First, if the required sensitivity below 87% is sufficient for the intended application, CM V method could perform well in terms of low false detection rate (FDR<14%). Secondly, if the application requires a sensitivity between 87% and 92%, the three methods could perform in a similar way in terms o f performance, wh ich appro ximately corresponds to an FDR in the range of 14-19%. Finally, if a high sensitivity is required (92% up to 98%), BMT based method can be considered the most efficient and leads to significantly lower FDR values (19% to 23%) co mpared to other methods.

A new method for speech denoinsing and speeker recognition applied to cochlear protheses

The systems of automatic words recognitions are not stopping to evolve and to present significant... more The systems of automatic words recognitions are not stopping to evolve and to present significant performances. In this paper, we present a treatment of speech intended to the cochlear prostheses. The technique used for this approach is the subbands speech recognition, the general principle is to split the whole frequency domain into several subbands on which statistical recognizers are independently applied. We also study which information is really used to recognize speakers. Nevertheless, the extent of the calculations is very important and complex in particular to the classification phase. We are interested to the sturdiness of the parameterisation technique cepstral coding and to the classification by the HMMs models.

New Approach of Speech Phonetic Segmentation Applied at Arabic Language

In the light of current scientific knowledge, the development of several speech treatment fields ... more In the light of current scientific knowledge, the development of several speech treatment fields has in parallel evolved with a huge amount of researches concerning automatic speech segmentation. In this paper we investigate the development of a precise speech segmentation system, especially applied on Arabic language. The main goal of this work is to implement an algorithm which is able to perform phonetic segmentation of speech, without prior knowledge of the phoneme sequence contained in the signal. We use for that a set of pertinent features to get the better rate recognition normal in the disturbed conditions. The segmentation algorithm achieved above standard quality results compared to what is found in current literature regarding blind segmentation.

Survey Of Temperature Variation Effect On Underwater Acoustic Wireless Transmission

In acoustic channel it is known that low available bandwidth, highly varying multipath, large pro... more In acoustic channel it is known that low available bandwidth, highly varying multipath, large propagation delays, noise and physical channel properties variation, in addition to the power consumption restrict the efficiency of underwater wireless acoustic systems. The physical characteristics of Mediterranean channel such as depth, salinity and especially temperature influence the acoustic signal attenuation, the SNR level, error ratio and the signal bandwidth. It seems to be crucial to introduce these parameters in the underwater channel model of the underwater wireless communication network. The goal of this paper is to highlight the impact of the temperature variation at shallow sea on the acoustic signal attenuation and error ratio and explain the relationship between temperature and SNR as well as the optimal frequency of the transmitted signal.