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Estudo e implementação de um analisador de harmônicos variantes no tempoMartins, Carlos Henrique Nascimento 26 March 2015 (has links)
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Previous issue date: 2015-03-26 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Esta tese apresenta as etapas de desenvolvimento de um sistema de monitoramento de parâmentos de qualidade de energia dedicado a análise de harmônicos variantes no tempo através do equipamento denominado AHVT (Analisador de Harmônicos Variantes no Tempo). O desenvolvimento do trabalho é composto por: (i) estudo e implementação MATLAB de algoritmos para processamento em tempo real, com capacidade de sintonização dos componentes harmônicos; (ii) análise e desenvolvimento de estratégias para detecção e validação da presença de interharmônicos próximos à frequência fundamental e suas consequência na estimação de parâmetros como fase, amplitude e frequência para o componente fundamental, (iii) proposta de implementação do dispositivo, sistema de aquisição/ condicionamento de sinais/ filtragem, sistema de conversão analógico digital e plataforma de processamentoDSP/FPGA, sistema de transmissão de dados e plataformas de análise online/offline dos eventos de harmônicos variantes no tempo; (iv) plataforma de simulação do Analisador de Harmônicos Variantes no Tempo (AHVT) para estudo dos métodos de trigger para detecção e captura dos eventos. / In this work is presented the steps of development and implementation of a Power Quality paramaters monitoring system with main goal events denomined ”time arying harmonics”named of Time Varying Harmonic Analyzer.
The development is comprises:(i) research and implementation of real time algorithms with capable to tuning harmonic waves,(ii) Analyze and research/development of strategies for detect and validation of interharmonics with frequencies near of fundamental, and conseguencies and challenges to phase, magnitude and frequency estimation with presence interharmonic waveform (iii) The proposal of a hardware design including analog to digital conversion and digital signal processing plataform, broadcast data link and IHM(Interface Human Machine) for online and offline analyzes to time varying harmonic analyzer;(iiii)off-line simulation plataform of Analisador de Harmônicos Variantes no Tempo Time Varying Harmonic Analyzer (TVHA) to trigger detect methods to detection and capture of waveforms.
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Contrôle modal autoadaptatif de vibrations de structures évolutives / Self-adaptive modal control of vibrations for time-varying structuresDeng, Fengyan 30 May 2012 (has links)
L’allègement des structures imposé par les réductions de coût se traduit par des structures de plus en plus souples qui les rendent de plus en plus sensibles aux vibrations. Le contrôle des vibrations devient donc un enjeu majeur dans de nombreuses applications industrielles et les limites des matériaux imposent maintenant un recours au contrôle actif de plus en plus fréquent. L’évolution des structures au cours du temps (viellisement, conditions aux limites, architecture, …) pose le problème de la robustesse du contrôle. Par ailleurs, l’actionnement de plus en plus présent dans le domaine mécanique constitue à la fois une source supplémentaire de vibrations, mais aussi de contrôle et d’évolution d’architecture des structures. La thèse s’intéresse au contrôle actif autoadaptatif des vibrations permettant de maintenir automatiquement la performance et la stabilité des structures évolutives. Il s’agit donc de s’affranchir de la connaissance des causes et des informations sur les évolutions. La méthode proposée s’appuie sur un développement modal permettant de limiter le nombre de composants de contrôle et de cibler les modes à contrôler en limitant l’énergie de contrôle. Ainsi, il est nécessaire de reconstruire les caractéristiques du modèle modal indispensables pour réactualiser le contrôle en figeant seulement une structure de modèle. S’affranchissant à la fois des causes d’évolution de la structure et utilisant seulement une structure de modèle, la méthode est généralisable à toute application en mécanique des structures. La méthode proposée, basée sur l’utilisation d’un identificateur exploitant à la fois excitation et réponse de la structure, prend en compte les limites imposées par le contrôleur. Le modèle constitue le lien qui doit être établi entre identificateur et contrôle pour permettre la réactualisation. Par ailleurs, un compromis entre l’objectif d’atténuation des vibrations et les performances de l’identification est alors nécessaire du fait du couplage identification/contrôle apparaissant dans la boucle fermée. Ce compromis est également conditionné par le matériel utilisé. La méthode proposée est exploitée sur une structure discrète mettant en évidence une inversion de formes modales au cours de son évolution qui déstabilise un contrôle figé. Le choix opéré pour répondre aux différents compromis cités ci dessus a conduit à l’utilisation d’un contrôleur classique (LQG) et un identificateur basé sur la méthode des sous-espaces (N4SID). Cette application sur une structure simple a permis de caractériser un certain nombre de limites physiques : la bande passante, densité modale, vitesse d’évolution, Le contrôle modal autoadaptatif proposé s’avère robuste en performance et efficace lorsque la réactualisation est systématique. Une variante conditionnelle, toujours basée sur l’analyse de la réponse de la structure, est enfin proposée pour optimiser le processus de réactualisation afin de suivre plus efficacement les évolutions. / The lightness of structure due to the reduction of cost results in some structures which are more and more flexible. This flexibility makes these structures more sensitive to vibrations. The vibration control becomes an important issue in lots of industrial applications, and now the limitation of materials imposes a requirement of active control more and more frequently.The change of time-varying structure(ageing effect, boundaries conditions, architecture of structure etc)brings the robust problem of control.Further more,the action of device which emerges more and more frequently in mechanical fields introduces not only an additional cause of vibrations,but also a source of control and a source for changing the architecture of structures.The thesis focuses on self-adaptive active control of vibration which permits to keep up automatically the performance and stability of the time-varying structures.So it needs to overcome the knowing about cause and information on the changes.The proposed method relies on a development of modal technology which permits to limit the amount of component in control system and to target on the modes which need to be controlled.So the energy of control is limited. Further more,it needs to reconstruct the characteristics of modal model which are indispensable for updating the control.In this case, only the structure of model is fixed.Overcoming the knowing about cause of change in the structure and using only the structure of model, this method can be generalized for all applications in mechanical structures.The proposed method is based on the utilization of an identifier which uses both the excitation and response of the structure.And this method considers the limitations induced by the controller.The model forms le link which should be established between the identifier and the controller for allowing the updating. Further more, a compromise between the objective of reducing vibrations and the performance of identification is necessary due to the coupling effect of identification/control which appears in the closed-loop. This compromise is also conditioned by the used equipments.The proposed method is carried out on a discrete time-varying structure for showing an inversion of mode shape during its change. This inversion of mode shape destabilises a fixed control system. The operated choices for responding the different previous quoted compromise lead to a classic controller (LQG) and an identifier based on the subspace method (N4SID).This application on a simple structure permitted to characterise some physical limitation: the bandwidth, the modal density and the velocity of change…The proposed self-adaptive modal control is proved to be robust in terms of performance and be efficient when the updating is systematical. Always based on the analysis of the response of the structure, a conditional variant is finally proposed for optimizing the process of updating in order to follow the change more efficiently.
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Autour des groupes tolérants aux délais dans les flottes mobiles communicantes / On Delay-Tolerant Groups in Communicating Mobile FleetsBarjon, Matthieu 01 December 2016 (has links)
Parmi les évolutions majeures de l'informatique, nous distinguons l'émergence des technologies mobiles sans fil. Le développement actuel de ces technologies permet de réaliser des communications ad-hoc directes entre de nombreux types d'entités mobiles, comme des véhicules, des robots terrestres ou des drones. Dans un réseau de tels équipements, l'ensemble des liens de communication qui existe à un instant donné dépend des distances entre les entités et la topologie du réseau change continuellement lorsque les entités se déplacent. Les hypothèses habituelles sur la connexité du réseau n'ont pas leur place ici, néanmoins, une autre forme de connexité appelée connexité temporelle est souvent disponible à travers le temps et l'espace. L'objectif de cette thèse a été de développer des algorithmes pour les flottes d'appareils dans le cas des réseaux tolérant aux délais (DTN). De manière simplifiée, les réseaux tolérants aux délais sont des réseaux pour lesquels certaines parties peuvent se retrouver isolées pendant un moment sans que cela pose problème. Nous nous intéressons, en particulier, au cas où ces appareils sont organisés sous la forme de groupes, et où la notion de groupe elle même survit à ces déconnexions transitoires. Ainsi, une grande partie de la thèse s'articule autour de la notion des groupes tolérant aux délais (groupe DTN). Dans notre cas cet éloignement est limité dans le temps et nous parlons alors de "diamètre temporel borné" au sein du groupe. Le fait de borner le diamètre temporel du groupe lui permet de distinguer entre l'éloignement temporaire d'un noeud et sa perte définitive (crash ou autre). / Among the major developments in computer science, we distinguish the emergence of mobile wireless technologies. The current development of these technologies allows for direct ad-hoc communications between many types of mobile entities, such as vehicles, land robots or drones. In a network of such devices, the set of communication links that exists at a given instant depends upon the distances between the entities. As a result, the topology of the network changes continuously as the entities move. The common assumption on connectivity may not be relevant in this case, but another kind of connectivity called temporal connectivity is often alvailable over time and space. The goal of this thesis has been the development of algorithms for fleets of mobile devices in the case of delay-tolerant networks. In a simpler way, the delay-tolerant networks are networks where some parts can be isolated during a certain time without problems. We are interested, in particular, in the case where the devices are organised as groups, and where the notion of group itself survives to these deconnections. Hence, a big part of this thesis relates to the notion of delay-tolerant groups (DTN groups). In our case, these deconnections are limited in time and we speak of a "bounded temporal diameter" within the group. The fact of limiting the temporal diameter of the group enables it to distinguish between temporary deconnections and final loss (crash or other) of some nodes.
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Importance ranking of parameter uncertainties in geo-hazard assessments / Analyse de sensibilité des incertitudes paramétriques dans les évaluations d’aléas géotechniquesRohmer, Jérémy 16 November 2015 (has links)
Les incertitudes épistémiques peuvent être réduites via des études supplémentaires (mesures labo, in situ, ou modélisations numériques, etc.). Nous nous concentrons ici sur celle "paramétrique" liée aux difficultés à évaluer quantitativement les paramètres d’entrée du modèle utilisé pour l’analyse des aléas géotechniques. Une stratégie de gestion possible est l’analyse de sensibilité, qui consiste à identifier la contribution (i.e. l’importance) des paramètres dans l’incertitude de l’évaluation de l’aléa. Des approches avancées existent pour conduire une telle analyse. Toutefois, leur application au domaine des aléas géotechniques se confronte à plusieurs contraintes : 1. le coût calculatoire des modèles numériques (plusieurs heures voire jours) ; 2. les paramètres sont souvent des fonctions complexes du temps et de l’espace ; 3. les données sont souvent limitées, imprécises voire vagues. Dans cette thèse, nous avons testé et adapté des outils statistiques pour surmonter ces limites. Une attention toute particulière a été portée sur le test de faisabilité de ces procédures et sur la confrontation à des cas réels (aléas naturels liés aux séismes, cavités et glissements de terrain) / Importance ranking of parameter uncertainties in geo-hazard assessments Epistemic uncertainty can be reduced via additional lab or in site measurements or additional numerical simulations. We focused here on parameter uncertainty: this corresponds to the incomplete knowledge of the correct setting of the input parameters (like values of soil properties) of the model supporting the geo-hazard assessment. A possible option tomanage it is via sensitivity analysis, which aims at identifying the contribution (i.e. the importance) of the different input parameters in the uncertainty on the final hazard outcome. For this purpose, advanced techniques exist, namely variance-basedglobal sensitivity analysis. Yet, their practical implementation faces three major limitations related to the specificities of the geo-hazard domain: 1. the large computation time cost (several hours if not days) of numerical models; 2. the parameters are complex functions of time and space; 3. data are often scarce, limited if not vague. In the present PhD thesis, statistical approaches were developed, tested and adapted to overcome those limits. A special attention was paid to test the feasibility of those statistical tools by confronting them to real cases (natural hazards related to earthquakes, cavities and landslides)
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Design and performance evaluation of a full rate, full diversity space-time-spreading code for an arbitrary number of Tx antennasMaasdorp, Francois De Villiers 18 September 2008 (has links)
Since the mid 1990’s, the wireless communications industry has witnessed explosive growth. The worldwide cellular and personal communication subscriber base surpassed 600 million users by late 2001, and the number of individual subscribers surpassed 2 billion at the end of 2006 [1, 2]. In order to attract and accommodate these subscribers, modern communication systems, like the Third Generation (3G) and Fourth Generation (4G) cellular networks, will have to provide attractive new features such as increased data throughput rates, greater system capacity, and better speech quality. These modern communication systems promise to have advantages such as wireless access in ways that have never been possible before, providing, amongst others services such as live television (TV) broadcasting to Mobile Stations (MS)s, multi-megabit Internet access, communication using Voice over Internet Protocol (VoIP), unparalleled network capacity, seamless accessibility and many more. With specific, but not exclusive reference to the cellular environment, there are numerous ways to increase the data throughput rate and system capacity. From an economical perspective, it would be more efficient to add equipment to the Base Station (BS) rather than the MSs. To achieve these improvements the motivation to utilise transmit diversity’s capabilities have been identified as a key research issue in this study. Alamouti [3] proposed a transmit diversity technique using two transmit antennas and one receive antenna, providing the same diversity order than using one transmit antenna and two receive antennas. Since Alamouti’s publication in 1998, many papers in the field of Space-Time (ST) coding have been published. Current research in the field of ST coding consists of finding methods to extend the number of transmit antennas to more than four, while still achieving full rate, as well as full diversity which is the main motivation for this study. This study proposes a novel idea of breaching the limitations with ST coding theory by combining ST coding with Spread Spectrum (SS) modulation techniques in order to extend the number of transmit antennas to more than four and still achieve full rate as well as full diversity. An advantage of the proposed scheme, called Direct Sequence Space-Time Spreading (DSSTS) has over current Space-Time Spreading (STS) techniques is that it uses 50% less spreading codes. A performance evaluation platform for the DSSTS scheme was developed to simulate the performance of the scheme in a realistic mobile communication environment. A mobile communication channel that has the ability to simulate time-varying multipath fading was developed and used to evaluate the performance of the DSSTS scheme. From the simulation results obtained, it is evident that Walsh sequences that exhibit particularly good cross-correlation characteristics, cannot overcome the effect of the antenna self-noise in order to exploit the diversity gain by adding extra antennas, i.e. diversity extension. The research also showed that an optimal trade-off exists between antenna diversity and antenna created self-noise. Performance results of the DSSTS scheme in slow and fast fading channels for a different number of transmit antennas are also presented in this study. With the capacity analysis of the DSSTS scheme, it was shown that the addition of extra transmit antennas to the system indeed increased the system capacity. A further addition to this study is the investigation into the assumption that the channel should be quasi-static over the frame length of the ST code. A Space Sequence Transmit Diversity (SSTD) technique is consequently proposed that allows the transmission of the Alamouti symbols during one time interval instead of two. This relieves the ST code from the assumption that the channel should be quasi-static, allowing it to be used in a more realistic multi-user environment. A performance evaluation platform for the SSTD scheme was developed and used to obtain simulation results in a multipath fading channel. It was also shown that the proposed SSTD scheme is successful in combating the effects of multipath fading for small Code Division Multiple Access (CDMA) user loads. However, as a rule of thumb, the square root of the spreading sequence length divided by two depicts the user load at which the SSTD scheme was not capable of overcoming the combined effects of Multi-User Interference (MUI) and multipath fading. / Dissertation (MEng)--University of Pretoria, 2008. / Electrical, Electronic and Computer Engineering / unrestricted
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Expectation-Maximization (EM) Algorithm Based Kalman Smoother For ERD/ERS Brain-Computer Interface (BCI)Khan, Md. Emtiyaz 06 1900 (has links) (PDF)
No description available.
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Nonstationary Techniques For Signal Enhancement With Applications To Speech, ECG, And Nonuniformly-Sampled SignalsSreenivasa Murthy, A January 2012 (has links) (PDF)
For time-varying signals such as speech and audio, short-time analysis becomes necessary to compute specific signal attributes and to keep track of their evolution. The standard technique is the short-time Fourier transform (STFT), using which one decomposes a signal in terms of windowed Fourier bases. An advancement over STFT is the wavelet analysis in which a function is represented in terms of shifted and dilated versions of a localized function called the wavelet. A specific modeling approach particularly in the context of speech is based on short-time linear prediction or short-time Wiener filtering of noisy speech. In most nonstationary signal processing formalisms, the key idea is to analyze the properties of the signal locally, either by first truncating the signal and then performing a basis expansion (as in the case of STFT), or by choosing compactly-supported basis functions (as in the case of wavelets). We retain the same motivation as these approaches, but use polynomials to model the signal on a short-time basis (“short-time polynomial representation”). To emphasize the local nature of the modeling aspect, we refer to it as “local polynomial modeling (LPM).”
We pursue two main threads of research in this thesis: (i) Short-time approaches for speech enhancement; and (ii) LPM for enhancing smooth signals, with applications to ECG, noisy nonuniformly-sampled signals, and voiced/unvoiced segmentation in noisy speech.
Improved iterative Wiener filtering for speech enhancement
A constrained iterative Wiener filter solution for speech enhancement was proposed by Hansen and Clements. Sreenivas and Kirnapure improved the performance of the technique by imposing codebook-based constraints in the process of parameter estimation. The key advantage is that the optimal parameter search space is confined to the codebook. The Nonstationary signal enhancement solutions assume stationary noise. However, in practical applications, noise is not stationary and hence updating the noise statistics becomes necessary. We present a new approach to perform reliable noise estimation based on spectral subtraction. We first estimate the signal spectrum and perform signal subtraction to estimate the noise power spectral density. We further smooth the estimated noise spectrum to ensure reliability. The key contributions are: (i) Adaptation of the technique for non-stationary noises; (ii) A new initialization procedure for faster convergence and higher accuracy; (iii) Experimental determination of the optimal LP-parameter space; and (iv) Objective criteria and speech recognition tests for performance comparison.
Optimal local polynomial modeling and applications
We next address the problem of fitting a piecewise-polynomial model to a smooth signal corrupted by additive noise. Since the signal is smooth, it can be represented using low-order polynomial functions provided that they are locally adapted to the signal. We choose the mean-square error as the criterion of optimality. Since the model is local, it preserves the temporal structure of the signal and can also handle nonstationary noise. We show that there is a trade-off between the adaptability of the model to local signal variations and robustness to noise (bias-variance trade-off), which we solve using a stochastic optimization technique known as the intersection of confidence intervals (ICI) technique. The key trade-off parameter is the duration of the window over which the optimum LPM is computed.
Within the LPM framework, we address three problems: (i) Signal reconstruction from noisy uniform samples; (ii) Signal reconstruction from noisy nonuniform samples; and (iii) Classification of speech signals into voiced and unvoiced segments.
The generic signal model is
x(tn)=s(tn)+d(tn),0 ≤ n ≤ N - 1.
In problems (i) and (iii) above, tn=nT(uniform sampling); in (ii) the samples are taken at nonuniform instants. The signal s(t)is assumed to be smooth; i.e., it should admit a local polynomial representation. The problem in (i) and (ii) is to estimate s(t)from x(tn); i.e., we are interested in optimal signal reconstruction on a continuous domain starting from uniform or nonuniform samples.
We show that, in both cases, the bias and variance take the general form:
The mean square error (MSE) is given by
where L is the length of the window over which the polynomial fitting is performed, f is a function of s(t), which typically comprises the higher-order derivatives of s(t), the order itself dependent on the order of the polynomial, and g is a function of the noise variance. It is clear that the bias and variance have complementary characteristics with respect to L. Directly optimizing for the MSE would give a value of L, which involves the functions f and g. The function g may be estimated, but f is not known since s(t)is unknown. Hence, it is not practical to compute the minimum MSE (MMSE) solution. Therefore, we obtain an approximate result by solving the bias-variance trade-off in a probabilistic sense using the ICI technique. We also propose a new approach to optimally select the ICI technique parameters, based on a new cost function that is the sum of the probability of false alarm and the area covered over the confidence interval. In addition, we address issues related to optimal model-order selection, search space for window lengths, accuracy of noise estimation, etc.
The next issue addressed is that of voiced/unvoiced segmentation of speech signal. Speech segments show different spectral and temporal characteristics based on whether the segment is voiced or unvoiced. Most speech processing techniques process the two segments differently. The challenge lies in making detection techniques offer robust performance in the presence of noise. We propose a new technique for voiced/unvoiced clas-sification by taking into account the fact that voiced segments have a certain degree of regularity, and that the unvoiced segments do not possess any smoothness. In order to capture the regularity in voiced regions, we employ the LPM. The key idea is that regions where the LPM is inaccurate are more likely to be unvoiced than voiced. Within this frame-work, we formulate a hypothesis testing problem based on the accuracy of the LPM fit and devise a test statistic for performing V/UV classification. Since the technique is based on LPM, it is capable of adapting to nonstationary noises. We present Monte Carlo results to demonstrate the accuracy of the proposed technique.
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Performance Analysis of Opportunistic Selection and Rate Adaptation in Time Varying ChannelsKona, Rupesh Kumar January 2016 (has links) (PDF)
Opportunistic selection and rate adaptation play a vital role in improving the spectral and power efficiency of current multi-node wireless systems. However, time-variations in wireless channels affect the performance of opportunistic selection and rate-adaptation in the following ways. Firstly, the selected node can become sub-optimal by the time data transmission commences. Secondly, the choice of transmission parameters such as rate and power for the selected node become sub-optimal. Lastly, the channel changes during data transmission.
In this thesis, we develop a comprehensive and tractable analytical framework that accurately accounts for these effects. It differs from the extensive existing literature that primarily focuses on time-variations until the data transmission starts. Firstly, we develop a novel concept of a time-invariant effective signal-to-noise ratio (TIESNR), which tractably and accurately captures the time-variations during the data transmission phase with partial channel state information available at the receiver. Secondly, we model the joint distribution of the signal-to-noise ratio at the time of selection and TIESNR during the data transmission using generalized bivariate gamma distribution.
The above analytical steps facilitate the analysis of the outage probability and average packet error rate (PER) for a given modulation and coding scheme and average throughput with rate adaptation. We also present extensive numerical results to verify the accuracy of each step of our approach and show that ignoring the correlated time variations during the data transmission phase can significantly underestimate the outage probability and average PER, whereas it overestimates the average throughput even for packet durations as low as 1 msec.
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Rychlé číslicové filtry pro signály EKG / Fast Digital filters for ECG SignalsRáček, Tomáš January 2011 (has links)
In the thesis there are described the implementations of various types of filters to remove disturbing signals, which often degrade the ECG signal. In particular, it is a zero isoline fluctuations and power network interference. It is used a principle of the Lynn’s linear filters. The individual filters are designed in a recursive and non-recursive implementation. Then there is described a time-varying linear Lynn's filter for removing drift of zero isoline signal. The thesis also includes filters with minimized calculating time of response, by sampling rate conversion method for both interference types. In conclusion there is an experimental study of the filter implementation for ECG signal with false and real interferences.
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Modélisation spatio-temporelle du trafic routier en milieu urbain / Spatio-temporal modeling of urban road trafficOberoi, Kamaldeep Singh 18 November 2019 (has links)
Le domaine de la modélisation du trafic routier vise à comprendre son évolution. Dans les dernières années, plusieurs modèles du trafic ont été proposés dans l’objectif de géolocaliser les embouteillages au sein du trafic, détecter des motifs dans le trafic routier, estimer l’état du trafic etc. La plupart des modèles proposés considèrent le trafic routier en termes de ses constituants ou comme une entité agrégée en fonction de l’échelle choisie et expliquent l’évolution du trafic quantitativement en tenant compte des relations entre les variables de trafic comme le flot, la densité et la vitesse. Ces modèles décrivent le trafic en utilisant des données très précises acquises par différents capteurs. La précision des données rend son calcul coûteux en termes de ressources requises. Une des solutions à ce problème est la représentation qualitative du trafic routier qui réduit le nombre de ressources de traitement nécessaires. Puisque le trafic routier est un phénomène spatio-temporel, les modèles proposés pour représenter ce type de phénomène pourraient être appliqués dans le cas du trafic routier. Les modèles spatio-temporels, proposés par la communauté de l’Analyse Spatio-Temporelle, ont comme objectif la représentation d’un phénomène tant du point de vue qualitatif que quantitatif. Certains de ces modèles proposent une discrétisation des phénomènes modélisés en considérant un phénomène comme constitué d’entités. Appliquée au trafic routier, cette notion permet d’identifier différentes entités, comme les véhicules, les piétons, les bâtiments etc., qui le constituent. Ces entités influent sur l’évolution du trafic. Les modèles spatio-temporels qualitatifs définissent l’effet des différentes entités les unes sur les autres en terme de relations spatiales. L’évolution spatio-temporelle du phénomène modélisé est représenté par la variation temporelle de ces relations. La prise en compte des entités du trafic et des relations spatiales formalise une structure qui peut être représentée en utilisant un graphe, où les nœuds modélisent des entités et les arcs des relations spatiales. Par conséquent, l’évolution du trafic, modélisée via ce graphe, devient l’évolution du graphe et peut être représenté en terme de la variation de la structure du graphe ainsi que celle des attributs de ses nœuds et de ses arcs. Dans cette thèse, nous proposons une modélisation du trafic routier de ce type basée sur la théorie des graphes. Une des applications à la modélisation du trafic routier est la détection des motifs pertinents au sein du trafic. Dans les modèles du trafic existants, les motifs détectés sont statistiques et sont représentés en utilisant des caractéristiques numériques. Le modèle que nous pro posons dans cette thèse met en avant la structure représentant le trafic routier et peut donc être utilisé pour définir des motifs structurels du trafic qui prennent en compte des différentes entités du trafic et leurs relations. Ces motifs structurels sont sous-jacents à une modélisation sous forme de graphe dynamique. Dans cette thèse, nous proposons un algorithme pour détecter ces motifs structurels du trafic dans le graphe spatio-temporel représentant le trafic routier. Ce problème est formalisé comme celui de l’isomorphisme de sous-graphe pour des graphes dynamiques. L’algorithme proposé est évalué en fonction desdifférents paramètres de graphes. / For past several decades, researchers have been interested in understanding traffic evolution, hence, have proposed various traffic models to identify bottleneck locations where traffic congestion occurs, to detect traffic patterns, to predict traffic states etc. Most of the existing models consider traffic as many-particle system, describe it using different scales of representation and explain its evolution quantitatively by deducing relations between traffic variables like flow, density and speed. Such models are mainly focused on computing precise information about traffic using acquired traffic data. However, computation of such precise information requires more processing resources. A way to remedy this problem is to consider traffic evolution in qualitative terms which reduces the required number of processing resources. Since traffic is spatio-temporal in nature, the models which deal with spatio-temporal phenomenon can be applied in case of traffic. Such models represent spatio-temporal phenomenon from qualitative as well as quantitative standpoints. Depending on the intended application, some models are able to differentiate between various entities taking part in the phenomenon, which proves useful in case of traffic since different objects like vehicles, buildings, pedestrians, bicycles etc., directly affecting traffic evolution, can be included in traffic models. Qualitative spatio-temporal models consider the effects of different entities on each other in terms of spatial relations between them and spatio-temporal evolution of the modeled phenomenon is described in terms of variation in such relations over time. Considering different traffic constituents and spatial relations between them leads to the formation of a structure which can be abstracted using graph, whose nodes represent individual constituents and edges represent the corresponding spatial relations. As a result, the evolution of traffic, represented using graph, is described in terms of evolution of the graph itself, i. e. change in graph structure and attributes of nodes and edges, with time. In this thesis, we propose such a graph model to represent traffic. As mentioned above, one of the applications of existing traffic models is in detecting traffic patterns. However, since such models consider traffic quantitatively, in terms of acquired traffic data, the patterns detected using such models are statistical (a term employed by Pattern Recognition researchers) in the sense that they are represented using numerical description. Since graph-based traffic model proposed in this thesis represents the structure of traffic, it can be employed to redefine the meaning of traffic patterns from statistical to structural (also a term from Pattern Recognition community). Structural traffic patterns include different traffic constituents and their inter-links and are represented using time-varying graphs. An algorithm to detect a given structural traffic pattern in the spatio-temporal graph representing traffic is proposed in this thesis. It formalizes this problem as subgraph isomorphism for time-varying graphs. In the end, the performance of the algorithm is tested using various graph parameters.
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