Dissertations / Theses on the topic 'DC algorithm'
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Zumberge, Jon T. "Validation of a DC-DC Boost Circuit Model and Control Algorithm." University of Dayton / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1435688617.
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Cai, Wei Kougianos Elias Mohanty Saraju. "FPGA prototyping of a watermarking algorithm for MPEG-4." [Denton, Tex.] : University of North Texas, 2007. http://digital.library.unt.edu/permalink/meta-dc-3695.
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Fernando, Pradeep R. "Genetic algorithm based two-dimensional and three-dimensional floorplanning for VLSI ASICs." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001549.
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Kaown, Dougsoo Liu Jianguo. "A new algorithm for finding the minimum distance between two convex hulls." [Denton, Tex.] : University of North Texas, 2009. http://digital.library.unt.edu/permalink/meta-dc-9845.
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Fernando, Pradeep Ruben. "Genetic algorithm based design and optimization of VLSI ASICs and reconfigurable hardware." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003289.
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Jones, Omar. "DESIGN AND DEVELOPMENT OF AN EMBEDDED DC MOTOR CONTROLLER USING A PID ALGORITHM." Thesis, Linköping University, Electronics System, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-58947.
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This project was held at London South Bank University in the UK, with corporation with staff from Linköping University in Sweden as Bachelor thesis.
This report will guide you through the used techniques in order to achieve a successful cooler/Fan project with a minimum budget and good energy saving methods.
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Sharma, Luetel Sadhana. "Performance analysis of a binary-tree-based algorithm for computing Spatial Distance Histograms." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003136.
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Xu, Yangyang. "Comparison of routing and network coding in group communications." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0002938.
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Samala, Ravi K. "Efficient suspicious region segmentation algorithm for computer aided diagnosis of breast cancer based on tomosynthesis imaging." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001800.
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Bouallagui, Sarra. "Techniques d'optimisation déterministe et stochastique pour la résolution de problèmes difficiles en cryptologie." Phd thesis, INSA de Rouen, 2010. http://tel.archives-ouvertes.fr/tel-00557912.
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Cette thèse s'articule autour des fonctions booléennes liées à la cryptographie et la cryptanalyse de certains schémas d'identification. Les fonctions booléennes possèdent des propriétés algébriques fréquemment utilisées en cryptographie pour constituer des S-Boxes (tables de substitution).Nous nous intéressons, en particulier, à la construction de deux types de fonctions : les fonctions courbes et les fonctions équilibrées de haut degré de non-linéarité.Concernant la cryptanalyse, nous nous focalisons sur les techniques d'identification basées sur les problèmes de perceptron et de perceptron permuté. Nous réalisons une nouvelle attaque sur le schéma afin de décider de sa faisabilité.Nous développons ici des nouvelles méthodes combinant l'approche déterministe DCA (Difference of Convex functions Algorithm) et heuristique (recuit simulé, entropie croisée, algorithmes génétiques...). Cette approche hybride, utilisée dans toute cette thèse, est motivée par les résultats intéressants de la programmation DC.
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Al, Kharboutly Mira. "Résolution d’un problème quadratique non convexe avec contraintes mixtes par les techniques de l’optimisation D.C." Thesis, Normandie, 2018. http://www.theses.fr/2018NORMLH06/document.
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Notre objectif dans cette thèse est de résoudre un problème quadratique binaire sous contraintes mixtes par les techniques d'optimisation DC. Puisque l'optimisation DC a prouvé son efficacité pour résoudre des problèmes de grandes tailles dans différents domaines, nous avons décidé d'appliquer cette approche d'optimisation pour résoudre ce problème. La partie la plus importante de l'optimisation DC est le choix d'une décomposition adéquate qui facilite la détermination et accélère la convergence de deux suites construites. La première suite converge vers la solution optimale du problème primal et la seconde converge vers la solution optimale du problème dual. Dans cette thèse, nous proposons deux décompositions DC efficaces et simples à manipuler. L'application de l'algorithme DC (DCA) nous conduit à résoudre à chaque itération un problème quadratique convexe avec des contraintes mixtes, linéaires et quadratiques. Pour cela, il faut trouver une méthode efficace et rapide pour résoudre ce dernier problème à chaque itération. Pour cela, nous appliquons trois méthodes différentes: la méthode de Newton, la programmation semi-définie positive et la méthode de points intérieurs. Nous présentons les résultats numériques comparatifs sur les mêmes repères de ces trois approches pour justifier notre choix de la méthode la plus rapide pour résoudre efficacement ce problèmeOur objective in this work is to solve a binary quadratic problem under mixed constraints by the techniques of DC optimization. As DC optimization has proved its efficiency to solve large-scale problems in different domains, we decided to apply this optimization approach to solve this problem. The most important part of D.C. optimization is the choice of an adequate decomposition that facilitates determination and speeds convergence of two constructed suites where the first converges to the optimal solution of the primal problem and the second converges to the optimal solution of the dual problem. In this work, we propose two efficient decompositions and simple to manipulate. The application of the DC Algorithm (DCA) leads us to solve at each iteration a convex quadratic problem with mixed, linear and quadratic constraints. For it, we must find an efficient and fast method to solve this last problem at each iteration. To do this, we apply three different methods: the Newton method, the semidefinite programing and interior point method. We present the comparative numerical results on the same benchmarks of these three approaches to justify our choice of the fastest method to effectively solve this problem
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Bailey, Troy D. "Modeling and implementing a digitally embedded maximum power point tracking algorithm and a series-loaded resonant DC-DC converter to integrate a photovoltaic array with a micro-grid." Thesis, Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/43870.
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Approved for public release; distribution is unlimitedA DC-DC converter with an embedded digital maximum power point tracking (MPPT) algorithm for a photovoltaic (PV) application is presented in this thesis. The topology centers around a series-loaded resonant (SLR) converter using galvanic isolation that interfaces a PV array with a storage battery connected to the DC bus of an existing micro-grid. The SLR converter operates in discontinuous conduction mode to minimize the switching losses and for the linear relationship between switching frequency and converter output current. This feature allows for multiple SLR converters to be paralleled, improving the overall efficiency of a PV system by eliminating a central converter and instituting the concept of multiple micro-converters. The perturb and observe MPPT algorithm employed uses a single voltage sensor and schedules a switching frequency based on the PV array power feedback. The performance of the MPPT algorithm is compared to a similar algorithm that uses both a current and voltage sensor. In this thesis, the SLR converter control system was simulated, designed, and implemented in the laboratory. The experimental measurements show that the SLR converter presented is an ideal topology for a PV application.
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Hersh, Lawrence T. "Mathematical techniques for the estimation of the diffusion coefficient and elimination constant of agents in subcutaneous tissue." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002035.
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Maxwell, Erick N. "Ultra-wideband electronics, design methods, algorithms, and systems for dielectric spectroscopy of isolated B16 tumor cells in liquid medium." [Tampa, Fla] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002172.
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Nagalakshmi, Subramanya. "Study of FPGA implementation of entropy norm computation for IP data streams." [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002477.
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Sopkin, Kristin L. "Heat fluxes in Tampa Bay, Florida." [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002398.
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Khan, Shoaib Amjad. "A hypergraph regularity method for linear hypergraphs." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003001.
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Štaffa, Jan. "Jednofázový pulzní měnič DC/AC s digitálním řízením." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-217881.
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This work is focused on single phase inverters, which are used for the conversion of the direct current to the alternating current and are nowdays used especially in systems of back-up power supply. The specific aim of this work is implementation of design hight power circuit of inverter include calculation of control algorithm. It describes the complete solution of power circuit. Next step is a analysis of problems concerning the digital control with help of signal processor which is used for solution of regulator structure. Check of the design and checkout of control algorithm is made in the form of simulation in the MATLAB Simulink. Debugged program algorithm is subsequently implemented into the signal microprocessor. The work results rate estimation functionality of inverter and solution of control algorithm.
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Olatoke, Abraham Oladele. "Impact of high penetration of renewable energy sources on the relay coordination of distribution system." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/12979.
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The rate at which the integration of distributed generation (DG) penetrates the public power supply has started to put various demands on the distribution system, since they are directly connected to the network. Distribution level protection is based on a time-overcurrent design. The design is to clear faults with as little impact and minimum time on the equipment and the customer. The increasing demands placed by grid services on the DGs, especially the PV types have a serious impact on the distribution system. For example, special protective devices are required to prevent the risk of danger in the event of mains interference. In this thesis, the main focus was on the contribution of fault currents to the distribution networks, and how the high penetration of DGs especially the renewable energy resources (R.E.S.) types affect the coordination of overcurrent (O.C.) protection. In view of the changes in the international regulations, the DGs are expected to stay connected and perform grid-related control functions, instead of shutting down at the first sign of a fault. This problem becomes more acute when the DGs stay connected during faults, known as voltage ride through (VRT). This thesis presented its findings on the impact of the DGs of various types of DGs (synchronous generator, asynchronous and power electronic) on the protection coordination by the high increase of fault currents, and the mitigation techniques of the impact of the inverter interfaced DGs (whose fault current contribution was not so high) on the overcurrent protection. The impact on system’s over-current protection coordination in such hybrid AC and DC microgrid, how the fault current changes by the high penetration of DGs in the hybrid microgrid and their effects on the protection over-current coordination were presented, as the name microgrid was adopted for networks having a point of common connection (PCC). The inverter interfaced-equipment were never in the conventional systems, the few that were there were all on the load side of the distribution system. The inverter interfacing DGs (PVs) and the synchronous types are the types of DGs that affect over-current protection of the distribution system and these were mitigated accordingly, considering the first few cycles of the fault events of the ride through capabilities. The analysis of the different penetration levels of the DGs in an existing 33kV in the Nigerian distribution network, (CocaCola-Challenge Industrial feeder) was thoroughly analysed, for less than 20%, more than 60% and 100% of the feeder load. Most of the DGs, presently existing in that network are the synchronous types, but they are only used as standby sources of power, and the renewables (RES) like the photovoltaics (PV), run of flow (RoF) Hydo and the wind turbine generators (WTG) are proposed additions. The objective of this thesis was to explain the fundamentals of distribution generation (DG) and especially the RES, in relation to distribution protection relay coordination to see why there should be urgency in carrying out the study especially in a developing environment where the grid is unstable, the load is rapidly expanding and RES is intermittent. The radial distribution system (DS) with high penetration of DG was introduced. The motive was to critically investigate protection coordination problems and the solutions to the problems. The main objective was to optimally recommend the type, size and location of the DG for an actual distribution feeder in an unstable environment where the grid supply is not steady. The effect of 100% and above of feeder load penetration on such feeders formed the objective of this research. The literature review which was for investigating in greater details the technical aspects of the operation and control of the high penetration of RES in the distribution system were thoroughly analysed. The review of the existing radial distribution protection system and the effects of high penetration of DG on the protective relaying were thoroughly investigated. The issues of power electronic based inverters and the protection coordination problems, were investigated. The protection coordination as regards to fault level changes and grounding, intentional and un-intentional islanding were major important aspects which were treated in the technical review.
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Hamann, Franz, and Gustavo Mesones. "Development of a hybrid system for automatic identification of brushed direct current motors." Institute of Electrical and Electronics Engineers Inc, 2020. http://hdl.handle.net/10757/656635.
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El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.This work proposes a low-cost hybrid hardware and software system that, through a set of methods and nested while loop fitting algorithms, allows to automatically identify the electrical and mechanical parameters of a brushed direct current motor. The aim is to facilitate a tool that contributes to the development of motion control projects in which this type of actuator is used, automating and speeding up the identification process of the motor system aiming to reach 98% accuracy, in order to guarantee a good electrical and mechanical parameter estimates for the brushed direct current motor. To achieve the objective, a platform was developed consisting of a main interface programmed in Matlab and a data acquisition hardware based on a single-phase incremental optical encoder, an H-bridge, an optocoupler circuit, and a C language-programmed DSPIC30F2010. Both parts of the platform are interconnected through the authors' own serial communication protocol.
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Belghiti, Moulay Tayeb. "Modélisation et techniques d'optimisation en bio-informatique et fouille de données." Thesis, Rouen, INSA, 2008. http://www.theses.fr/2008ISAM0002.
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Cette thèse est particulièrement destinée à traiter deux types de problèmes : clustering et l'alignement multiple de séquence. Notre objectif est de résoudre de manière satisfaisante ces problèmes globaux et de tester l'approche de la Programmation DC et DCA sur des jeux de données réelles. La thèse comporte trois parties : la première partie est consacrée aux nouvelles approches de l'optimisation non convexe. Nous y présentons une étude en profondeur de l'algorithme qui est utilisé dans cette thèse, à savoir la programmation DC et l'algorithme DC (DCA). Dans la deuxième partie, nous allons modéliser le problème clustering en trois sous-problèmes non convexes. Les deux premiers sous-problèmes se distinguent par rapport au choix de la norme utilisée, (clustering via les normes 1 et 2). Le troisième sous-problème utilise la méthode du noyau, (clustering via la méthode du noyau). La troisième partie sera consacrée à la bio-informatique. On va se focaliser sur la modélisation et la résolution de deux sous-problèmes : l'alignement multiple de séquence et l'alignement de séquence d'ARN par structure. Tous les chapitres excepté le premier se terminent par des tests numériquesThis Ph.D. thesis is particularly intended to treat two types of problems : clustering and the multiple alignment of sequence. Our objective is to solve efficiently these global problems and to test DC Programming approach and DCA on real datasets. The thesis is divided into three parts : the first part is devoted to the new approaches of nonconvex optimization-global optimization. We present it a study in depth of the algorithm which is used in this thesis, namely the programming DC and the algorithm DC ( DCA). In the second part, we will model the problem clustering in three nonconvex subproblems. The first two subproblems are distinguished compared to the choice from the norm used, (clustering via norm 1 and 2). The third subproblem uses the method of the kernel, (clustering via the method of the kernel). The third part will be devoted to bioinformatics, one goes this focused on the modeling and the resolution of two subproblems : the multiple alignment of sequence and the alignment of sequence of RNA. All the chapters except the first end in numerical tests
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Ghamrawi, Ahmad. "Optimisation et gestion des flux énergétiques d'un générateur solaire photovoltaïque." Thesis, Poitiers, 2018. http://www.theses.fr/2018POIT2304.
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Cette thèse s'inscrit sur une thématique de recherche dédiée aux systèmes de production d'énergie solaire photovoltaïque. En effet, les besoins énergétiques mondiaux sont en croissance continue, l’exploitation et la consommation des énergies fossiles épuisent des ressources limitées et impactent notre environnement. L’énergie solaire photovoltaïque représente une source d'énergie renouvelable des plus prometteuse, même si ses inconvénients demeurent le coût élevé d'installation initiale et la variabilité de sa production. Les travaux présentés visent surtout à optimiser le rendement énergétique global d'un système solaire photovoltaïque non connecté au réseau. Ainsi, ce travail de recherche se focalise sur l’architecture de la chaîne de conversion avec l’intégration de convertisseurs élévateurs DC-DC conventionnel et quadratique et sur une optimisation des algorithmes de recherche du point de puissance maximale lors de variations des conditions climatiques. La modélisation et l’analyse de ces convertisseurs élévateurs sont conduites sous forme de systèmes à commutation afin de proposer une commande stabilisante aux points d’équilibre selon la définition de Lyapunov. Des résultats de simulation sous Matlab/SimulinkTM sont exposés, attestant la maximisation de la puissance électrique récupérée et la stabilité pour le point de fonctionnement. Des résultats expérimentaux, issus du banc expérimental du laboratoire LIAS, viennent corréler et confirmer l'intérêt des approches proposéesThis thesis in part of research thematic dedicated to photovoltaic solar energy production's systems. In fact, energy demands in the world are continuously increasing, the fossil fuels exploitation depletes limited sources and impact our environment. Solar photovoltaic energy represents one of the most promoted renewable energy sources, even if its drawbacks remain its installation’s high initial cost and its production’s variability. The main object of the presented work is to optimize the global efficiency of a stand-alone photovoltaic system. In that respect, this research focuses on the architecture of the conversion chain by integrating DC-DC conventional and quadratic boost converters and on the optimization of maximum power point tracking algorithms during fast changing weather conditions. These converters are modelling as switched affine systems to propose a switching rule that stabilize the operating point according to Lyapunav theory. Several simulation results using Matlab/SimulinkTM are given to declare the maximization of the extracted electrical power and the stability of the operating point. Experimental results recuperated on a test bench in the laboratory LIAS backed and confirmed the interest of the proposed approaches
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Dias, Rafael Nunes Hidalgo Monteiro. "Análise comparativa de técnicas de controle Fuzzy e matriz dinâmica aplicadas à máquina de corrente contínua." Universidade Federal de Goiás, 2017. http://repositorio.bc.ufg.br/tede/handle/tede/8098.
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This work presents a comparison between Fuzzy and dynamic matrix controllers. These controllers are applied to the direct current (DC) motor speed control, triggered by fully controlled three-phase rectifier. The construction of the real system and the development and validation of the computational model are described. The controllers’ parameters are obtained through an optimization process. Both control techniques are compared and results indicate better performance of the optimized controllers, which suggest their promise in nonlinear systems’ control, in which seeks out control without error, that fulfills well its duty and its able to resist the fatigues.
Este trabalho apresenta o comparativo entre os controladores Fuzzy e matriz dinâmica. Estes controladores são aplicados ao controle de velocidade do motor de corrente contínua, acionado por retificador trifásico totalmente controlado. A metodologia parte da construção do sistema real e do desenvolvimento e validação do modelo computacional. A obtenção dos parâmetros dos controladores é realizada através do processo de otimização. Realiza-se análise comparativa entre as técnicas de controle e os resultados apontam para a proeminência de controladores sintonizados via processo de otimização como técnica promissora a ser empregada em controle de sistemas não lineares, nos quais buscam-se controle em que não há erro, que cumpra bem o seu dever e apto para resistir às fadigas.
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Novák, Pavel. "Návrh řídicího algoritmu pro stabilizaci letadla." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2013. http://www.nusl.cz/ntk/nusl-230970.
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Master’s thesis: "Design of the control algorithm for aircraft stabilization" summarizes aircraft aerodynamics knowledge, from which nonlinear mathematical model of the aircraft and propeller propulsion system are created. Design of the control algorithm for angle position stabilization (for longitudinal motion) and the control algorithm for “Flight Path Angle hold“ and “Flight Level Change” modes is also presented here. Designed control algorithms are tested within the simulation of the real atmosphere at the end of the thesis.
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Valkanova, Elena. "Algorithms for simple stochastic games." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003070.
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Wang, Dian. "Microgrid based on photovoltaic energy for charging electric vehicle stations : charging and discharging management strategies in communication with the smart grid." Thesis, Compiègne, 2021. http://www.theses.fr/2021COMP2584.
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Le développement rapide des véhicules électriques (EVs) augmente la demande de puissance, ce qui provoque une charge supplémentaire sur le réseau public et augmente les fluctuations de la charge. Par conséquent, la forte pénétration des EVs est freinée. Un algorithme simulé en temps réel et basé sur des règles est élaboré pour les bornes de recharge des EVs alimentées par un micro-réseau DC afin de faire face aux incertitudes du comportement des utilisateurs des EVs. L'algorithme prend en considération les choix arbitraires et aléatoires proposés via l'interface homme-machine. Les résultats de simulation sont obtenus sous MATLAB / Simulink et vérifient la faisabilité de la stratégie de gestion proposée. Cette stratégie présente de bonnes performances en garantissant un contrôle précis. Par ailleurs, les algorithmes d'optimisation de délestage et de la restauration des EVs (SROA) pour la recharge de la puissance de la batterie peuvent être utilisés pour répondre aux besoins des utilisateurs. Aussi les algorithmes SROA maintiennent l'équilibre de la puissance de la station de recharge des EVs. Les algorithmes SROA prennent en compte l'intermittence de la source photovoltaïque (PV), la limitation de capacité du stockage et la limitation de puissance du réseau public. En comparant les résultats de la simulation aux algorithmes basés sur les règles, les algorithmes SROA proposés respectent le choix de l'utilisateur, réduisent le temps de charge total, augmentent le plein débit et maximisent l'utilisation de la puissance disponible. Les résultats de la simulation montrent la faisabilité et l'efficacité des algorithmes SROA. En outre, une station de charge basée sur le PV pour les EVs peut participer à la résolution de certains problèmes liés au pic de puissance. D'autre part, la technologie de véhicule à réseau (V2G) est conçue et appliquée pour fournir des services auxiliaires au réseau pendant les périodes de pointe, et V2G considère la dualité de la batterie des EVs « charge et source ». Ainsi, un algorithme de recherche dynamique des pics et de vallées est proposé pour une station de recharge des EVs afin d'atténuer l'impact sur le réseau public. Cet algorithme réduit ainsi le coût énergétique du réseau public. Les résultats de la simulation démontrent bien l'efficacité de l'algorithme de recherche des pics et des vallées. L'algorithme peut garantir l'équilibre du réseau public, satisfaire la demande de charge des utilisateurs des EVs et, surtout, réduire le coût énergétique du réseau publicThe rapid development of electric vehicles (EVs) increases the power demand, which causes an extra burden on the public grid increasing the load fluctuations, therefore, hindering the high penetration of EVs. A real-time rule-based algorithm for electric vehicle (EV) charging stations empowered by a DC microgrid is proposed to deal with the uncertainties of EV users’ behaviour considering its arbitrary and random choices through the human-machine interface, meanwhile considering most of the users’ choices. The simulation results obtained under MATLAB/Simulink verify the feasibility of the proposed management strategy that presents a good performance in terms of precise control. In addition, EV shedding and restoration optimization algorithms (SROA) for battery charging power can be used to meet user needs while maintaining EV charging station power balance, taking into consideration the intermittency of the photovoltaic (PV) source, the capacity limitation of the storage, and the power limitation of the public grid. The simulation results show that compared with rule-based algorithm, the proposed SROA respect the user's choice while reducing total charging time, increasing the full rate, and maximizing the available power utilization, which shows the feasibility and effectiveness of SROA. Furthermore, a PV based charging station for EVs can participate to solve some peak power problems. On the other hand, vehicle to grid (V2G) technology is designed and applied to provide ancillary services grid during the peak periods, considering the duality of EV battery “load-source”. So, a dynamic searching peak and valley algorithm, based on energy management, is proposed for an EV charging station to mitigate the impact on the public grid, while reducing the energy cost of the public grid. Simulation results demonstrate the proposed searching peak and valley algorithm effectiveness, which can guarantee the balance of the public grid, meanwhile satisfy the charging demand of EV users, and most importantly, reduce the public grid energy cost
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Thiao, Mamadou. "Approches de la programmation DC et DCA en data mining : modélisation parcimonieuse de données." Phd thesis, INSA de Rouen, 2011. http://tel.archives-ouvertes.fr/tel-00667179.
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Nous abordons dans cette thèse les approches de la Programmation DC et DCAen Data Mining (fouille de données). Plus particulièrement, nous nous intéressons aux problèmes de parcimonie en modélisation parcimonieuse de données. Le travail porte sur des recherches théoriques et algorithmiques et la principale approche utilisée est la programmation DC et DCA.Nous avons établi des propriétés intéressantes, des reformulations DC, voire quadratiques,équivalentes pour ces problèmes grâce à de nouvelles techniques de pénalité exacte développées durant cette thèse. Ces résultats donnent une nouvelle facette et une nouvelle manière de voir ces problèmes de parcimonie afin de permettre une meilleure compréhension et prise en main de ces problèmes. Ces nouvelles techniques ont été appliquées dans le cadre de la modélisation parcimonieuse pour le problème de la valeur propre maximale et dans le cadre de la modélisation parcimonieuse dans les modèles de régression linéaire.La structure simple des reformulations obtenues se prête bien à la programmation DC et DCA pour la résolution. Les simulations numériques, obtenues avec DCA et un algorithme combiné DCA et la procédure Séparation et Evaluation pour l'optimisation globale, sont très intéressantes et très prometteuses et illustrent bien le potentiel de cette nouvelle approche.
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Jenča, Pavol. "Identifikace parametrů elektrických motorů metodou podprostorů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219678.
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The electrical motors parameters identification is solved in this master’s thesis using subspace based methods. Electrical motors are simulated in Matlab/Simulink interactive environment, specifically permanent magnet DC motor and permanent magnet synchronous motor. Identification is developed in Matlab interactive environment. Different types of subspace algorithms are used for the estimation of parameters. Results of subspace parameters estimation are compared with least squares parameters estimation. The thesis describes subspace method, types of subspace algorithms, used electrical motors, nonlinear approach of identification and comparation of parameters identification.
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Sahin, Mustafa. "Baseband receiver algorithms for 4G co-channel femtocells." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003283.
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Sinha, Ravi Som Mihalcea Rada F. "Graph-based centrality algorithms for unsupervised word sense disambiguation." [Denton, Tex.] : University of North Texas, 2008. http://digital.library.unt.edu/permalink/meta-dc-9736.
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Zein, Eddine Abbass. "Algorithmes de détection et diagnostic des défauts pour les convertisseurs statiques de puissance." Thesis, Normandie, 2017. http://www.theses.fr/2017NORMLH28/document.
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Les convertisseurs DC-DC suscitent un intérêt considérable en raison de leur puissance élevée et de leurs bonnes performances. Ils sont particulièrement utiles dans les systèmes multisources de production d'énergie électrique. Toutefois, en raison du grand nombre de composants sensibles utilisés dans ces circuits et comprenant des semi-conducteurs de puissance, des bobines et des condensateurs, une probabilité non négligeable de défaillance des composants doit être prise en compte. Cette thèse considère l'un des convertisseurs DC-DC les plus prometteurs - le convertisseur ZVS à pont isolé de type Buck. Une approche en deux étapes est présentée pour détecter et isoler les défauts en circuit ouvert dans les semi-conducteurs de puissance des convertisseurs DC-DC. La première étape concerne la détection et la localisation des défauts dans un convertisseur donne. La seconde étape concerne sur les systèmes munis de plusieurs convertisseurs DC-DC. Les méthodes proposées sont basées sur les réseaux Bayesiens (BBN). Les signaux utilisés dans ces méthodes sont ceux des entrées de mesure du système de commande et aucune mesure supplémentaire n'est requise. Un convertisseur expérimental ZVS à pont isolé de type Buck a été conçu et construit pour valider la détection et la localisation des défauts Sur un seul convertisseur. Ces méthodes peuvent être étendues à d'autres types de convertisseurs DC-DCDC-DC converters have received significant interest recently as a result of their high power capabilities and good power quality. They are of particular interest in systems with multiple sources of energy. However due to the large number of sensitive components including power semiconductor devices, coils, and capacitors used in such circuits there is a high likelihood of component failure. This thesis considers one of the most promising DC-DC converters—the ZVS full bridge isolated Buck converter. An approach with two stages is presented to detect and isolate opencircuit faults in the power semiconductor devices in systems with DC-DC converters. The first stage is the fault detection and isolation for a single DC-DC converter, while the second stage works on a system with multiple DC-DC converters. The proposed methods are based on Bayesian Belief Network (BBN). The signals used in the proposed methods are already available as measurement inputs to control system and no additional measurements are required. An experimental ZVS full bridge isolated Buck converter has been designed and built to validate the fault detection and isolation method on a single converter. The methods can be used with other DC-DC converter typologies employing similar analysis and principals
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Zhou, Jun. "Synchronization Algorithms and VLSI Implementation for DC-OFDM based UWB System." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-66729.
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UWB is a promising technology for short-range high-rate wireless applicationa.It is able to providemaximal 480Mbps data-rate at a distance of 2 meters in realisticindoormulti-path environments. UWB technology is widely applied to the next generation WPAN as well as the wireless accessof consumer electronics at home. Recently, Multi-Band OFDM based UWB technology proposed by WiMedia has been selected as the international standard by ISO. In China, a new transmission architecture based on Dual-Carrier OFDM technology is adopted as UWB standard draft. Comparing to MB-OFDM based UWB system, DC-OFDM based UWB system has multiple advantages, like more spectrum resource,lower requirements on devices, etc. Besides, it is compatiblewith existing MB-OFDM based UWB technology. Therefore, DC-OFDM based UWB is more flexible. Synchronizationis the first step atthe receiver digital baseband, which is of tremendous importance in any wireless communication systems. The performance of synchronization directly determines whether the receiver can pick up radio signals correctly or not, whether the baseband modules can fulfill the digital signal processing effectively or not. The synchronization process in OFDM system can be briefly divided into two parts: symbol timing and frequency synchronization. Symbol timing serves to judge the starting position of OFDM symbolsafter considering the impact of multi-path fading channel.While the frequency synchronization estimates the multiple imperfections in analog front-end signal processing and make proper compensation. This thesis puts the emphasis on synchronization issues in DC-OFDM based UWB systems. We are the first to analyze the synchronization algorithm as well as the hardware implementation method tailored for DC-OFDM based UWB system. We also present the VLSI implementation result for synchronization module. The thesis consists of symbol timing and frequency synchronization. Regarding on the symbol timing, we analyze the impact of several synchronization errors inOFDM system. After that, we divide the synchronization process into four modulesby functionality: packet detection, coarse timing, TFC detection and fine timing. The internal parameters in each moduleare determined by system simulations. In the aspect of algorithm development, we adopt the joint auto-correlation and cross-correlation method to meet the requirements of UWB system in different indoor multi-path environments, and therefore achieve the robustness. In the aspect of hardware implementation, we put the attention on the structure of some key modules in symbol timing and their VLSI implementation result, such as auto-correlator, cross-correlator, real-number divider, etc. Regarding on the frequency synchronization, we first investigate the multiple analog front-end imperfections in OFDM system, like CFO, SFO and I/Q imbalance, and present their mathematics models respectively in DC-OFDM based UWB system.After that, we analyze the performance degradation in OFDM system due to these non-ideal effects by the metric of EVM. RF designer can build the connection between mismatching parameters and performance degradation by referring to the analysis. Hence, theRF designer is able to traceout the outline of system design. In the aspect of algorithm development, we explore the intrinsic character of I/Q imbalancewhich causes the image interference. Then, we design a set of new training sequences based on phase rotation and give the corresponding estimation algorithm.The simulation result shows that the new training sequence is able to obtain the diversity message introduced by I/Q imbalance and therefore achieve the diversity gain during demodulation process. In order to deal with the challenging situation where multiple analog front-end imperfections co-exist, we propose a joint estimation and compensation scheme. In the aspect of hardware implementation, we present the hardware structure of CFO estimation and compensation module catered for DC-OFDM based UWB system, with the emphasis on CORDIC unit that is responsible for triangle calculations. The VLSI implementation result shows that the proposed CFO estimation and compensation module satisfies the timing and resource requirements in DC-OFDM based UWB system. In the last, we present the prospective research area in 60-GHz applications. It includes multiplenon-ideal impairments, like phase noise, non-linear power amplification, DC offset, ADCs mismatch, etc. It is even more challenging to develop joint estimation and compensation scheme for these non-ideal effects.
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Arumugavelu, Shankar. "SIMD algorithms for single link and complete link pattern clustering." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0001967.
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Hanson, Ronald J. "Implementing Closed-Loop Control Algorithms for DC-to-DC Converters and ARCP Inverters Using the Universal Controller [electronic resource]." Ft. Belvoir Defense Technical Information Center, 1997. http://hdl.handle.net/10945/8509.
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The objective of this thesis is to investigate the use of the Universal Controller to control the DC-to-DC power converter and the Auxiliary Resonant Commutated Pole (ARCP) power inverter. These power electronic devices are central to the development of a DC Zonal Electric Distribution System (DC ZEDS) that is scheduled for application in the twenty-first century surface combatant (SC-21). The development of appropriate closed-loop controls is a key element to this design process. The Universal Controller is a digital controller that was developed by personnel at the Naval Surface Warfare Center (NSWC), Annapolis, Maryland. The basic operation and control of the DC-to-DC buck converter and the ARCP inverter are described, with emphasis placed on the advantages of DSP control. A complete investigation of the hardware that comprises the controller and how to program the controller to implement closed-loop control is undertaken. Previous studies have developed control algorithms that have been tested through simulation and analog hardware. In this research endeavor these control algorithms, particularly the one relevant to the DC-to-DC converter, are implemented using the Universal Controller to validate operations. Finally, a flow path for implementing the closed-loop control of the ARCP unit is discussed and recommendations for improvements in future designs are outlined
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Rider, Flores Marcos Julio 1975. "Planejamento da expansão de sistemas de transmissão usando os modelos CC - CA e tecnicas de programação não-linear." [s.n.], 2006. http://repositorio.unicamp.br/jspui/handle/REPOSIP/260508.
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Orientador: Ariovaldo Verandio Garcia, Ruben Augusto Romero LazaroTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação
Made available in DSpace on 2018-08-06T06:56:43Z (GMT). No. of bitstreams: 1 RiderFlores_MarcosJulio_D.pdf: 1021887 bytes, checksum: 6000961c2f5457b410ac691912476270 (MD5) Previous issue date: 2006
Resumo: Neste trabalho são propostos modelos matemáticos e técnicas de solução para resolver o problema de planejamento da expansão de sistemas de transmissão através de três enfoques. a) Usando o modelo de corrente alternada do sistema de transmissão e um algoritmo heurístico construtivo especializado para resolver o problema de planejamento, e, ainda, realiza-se uma primeira tentativa de alocação de fontes de potência reativas; b) Usando o modelo de corrente contínua e técnicas de programação não-linear especializadas. Nesse caso emprega-se uma versão relaxada do problema de planejamento da expansão de sistemas de transmissão usando o modelo de corrente contínua, onde a integralidade das variáveis de investimento é desprezada. Resolve-se o problema de programação não-linear, modelado de forma matricial com um algoritmo de otimização especializado e, além disso, um algoritmo heurístico construtivo especializado é utilizado para resolver o problema de planejamento. c) Usando o modelo de corrente contínua e um algoritmo Branch and Bound (B&B) sem empregar técnicas de decomposição. Para isso foram redefinidos os chamados testes de sondagem no algoritmo B&B e em cada nó da árvore de B&B tem-se um problema de programação não-linear que são resolvidos usando a metodologia desenvolvida no item (b). Os ítens (a), (b) e (c) requerem a solução de problemas de programação não-linear diferenciados. Uma revisão das características principais da resolução iterativa dos métodos de pontos interiores é apresentada. Foi desenvolvida uma técnica baseada em uma combinação de métodos de pontos interiores de alta ordem (MPI-AO) para resolver os problemas de programação não-linear de forma rápida, eficiente e robusta. Essa combinação dos MPI-AO tem como objetivo colocar num único método as características particulares de cada um dos MPI-AO e melhorar o desempenho computacional comparado com os MPI-AO de forma individual
Abstract: In this work mathematical models and solution techniques are proposed to solve the power system transmission expansion planning problem through three approaches: a) Using the nonlinear model ofthe transmission system (AC model) and a specialized constructive heuristic algorithm to solve the problem and, yet, a first attempt to allocate reactive power sources is also considered; b) Using the direct-current (DC) model and specialized techniques of nonlinear programming. In this case a version of the power system transmission expansion planning problem using the DC model where the integrality of the investment variables is relaxed is used. The nonlinear programming problem is solved with a specialized optimization algorithm and, moreover, a constructive heuristic algorithm is employed to solve the planning problem. c) Using the DC model and Branch and Bound (B&B) algorithm without the use of decomposition techniques. The so called fathoming tests of the B&B were redefined and at each node of the tree a nonlinear programming problem is solved using the method developed in b). Items a), b) and c) require the solution of distinct problems of nonlinear programming. A revision of the main characteristics of the iterative solution of the interior points methods is presented. An optimization technique based on a combination of the higher order interior point methods (HO-IPM) had been developed to solve the nonlinear programming problems in a fast, efficient and robust way. This combination of the HO-IPM has as objective to explore the particular characteristics of each method in a single one and to improve the comparative computational performance with the HO-IPM of individual form
Doutorado
Energia Eletrica
Doutor em Engenharia Elétrica
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Hore, Prodip. "Scalable frameworks and algorithms for cluster ensembles and clustering data streams." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002135.
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Bhattacharya, Koustav. "Architectures and algorithms for mitigation of soft errors in nanoscale VLSI circuits." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003280.
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Chotikorn, Nattapong. "Implementations of Fuzzy Adaptive Dynamic Programming Controls on DC to DC Converters." Thesis, University of North Texas, 2019. https://digital.library.unt.edu/ark:/67531/metadc1505139/.
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DC to DC converters stabilize the voltage obtained from voltage sources such as solar power system, wind energy sources, wave energy sources, rectified voltage from alternators, and so forth. Hence, the need for improving its control algorithm is inevitable. Many algorithms are applied to DC to DC converters. This thesis designs fuzzy adaptive dynamic programming (Fuzzy ADP) algorithm. Also, this thesis implements both adaptive dynamic programming (ADP) and Fuzzy ADP on DC to DC converters to observe the performance of the output voltage trajectories.
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Aldawoodi, Namir. "An approach to designing an unmanned helicopter autopilot using genetic algorithms and simulated annealing." [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002458.
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Floodeen, David L. "Using the PEBB universal Controller to modify control algorithms for DC-to-DC converters and implement closed-loop control of ARCP inverters." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1998. http://handle.dtic.mil/100.2/ADA355736.
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Thesis (M.S. in Electrical Engineering) Naval Postgraduate School, September 1998."September 1998." Thesis advisor(s): John G. Ciezki, Robert W. Ashton. Includes bibliographical references (p. 113-114). Also available online.
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Štěpánek, Jan. "Identifikace systému, sensorika a implementace řídicího algoritmu pro nestabilní balancující vozidlo." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2011. http://www.nusl.cz/ntk/nusl-229876.
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This work deals with design and construction of unstable double wheeled Segway-like vehicle built for human personnel transportation and its smaller scaled clone developed for control algorithms testing. The smaller machine is controlled via Joystick and PC. This work was conducted in team consisting of three students. Individual goals are described in chapter „Stanovení cílů práce“. The beginning of the work deals with researching any similar projects concerned with this topic, especially with sensors and control algorithms used. Further, the work describes the process of choosing used electronics and its parameters. One of the problems faced during the work was the pitch angle of the vehicle base calculation - algorithm of the angle calculation had been designed by students of several world universities. The principle of how it works was studied and then tested by simulations and practically in the following chapters. Further on, the work deals with platform‘s parameter estimation, at first the testing platform made of wood, followed by the final platform made of aluminium. Parameter estimation was realized by using the multifunctional I/O card Humusoft MF 624 for PC. Part of the work deals with the final control algorithm on the dsPIC microcontroller implementation, sensor‘s outputs calculation and calibration algorithm design. Since the vehicle is built for human personnel transportation, implementation of certain safety algorithms was necessary. These algorithms should be able to detect possible fail states and prevent the driver from losing control over the vehicle in order to prevent any injuries.
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Moeini, Mahdi. "La programmation DC et DCA pour l'optimisation de portefeuille." Thesis, Metz, 2008. http://www.theses.fr/2008METZ008S/document.
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Les travaux présentés dans cette thèse concernent les nouvelles techniques d'optimisation pour la résolution de certains problèmes importants issus de finance. Il s'agit des problèmes d'optimisation non convexe de grande dimension pour lesquels la recherche des bonnes méthodes de résolution est toujours d'actualité. Notre travail s'appuie principalement sur la programmation DC (Différence de fonctions Convexes) et DCA (DC Algorithmes). Cette démarche est motivée par la robustesse et la performance de la programmation DC et DCA comparée aux autres méthodes. La thèse est divisée en deux parties et est composée de sept chapitres. Dans la première partie intitulée ¡Méthodologie¡ nous présentons des outils théoriques et algorithmiques servant des références aux autres. Le premier chapitre concerne la programmation DC et DCA tandis que le deuxième porte sur les algorithmes par séparation et évaluation. Dans la deuxième partie nous développons la programmation DC et DCA pour la résolution des problèmes en finance. Nous commençons par une introduction à la gestion de portefeuille (le Chapitre 3). Le Chapitre 4 est dédié aux généralisations du modèle moyenne-variance (MV) de Markowitz, où nous étudions le modèle MV sous les contraintes de seuil d'achat, de seuil et de cardinalité. Le Chapitre 5 est consacré à la mesure de risque de baisse et les contraintes de cardinalité. Le Chapitre 6 porte sur le problème de choix de portefeuille avec les fonctions des coûts de transaction en escalier. L'investissement robuste en gestion de portefeuille sous les contraintes de cardinalité est développé dans le dernier chapitreThe topics presented in this thesis are related to new optimization techniques for solving some challenging problems resulting from finance. They are large-scale non convex optimization problems for which finding efficient solving methods is currently the topic of numerous researches. Our work is based mainly on DC (Difference of Convex functions) programming and DCA (DC Algorithm). This approach is motivated by the robustness and efficiency of DC programming and DCA approaches in comparison to the other methods. The thesis is divided into two parts and consists of seven chapters. In the first part entitled Methodology ; we present theoretical tools and algorithms that we are going to use in the thesis. The first chapter is about DC programming and DCA and the second focuses on branch and bound algorithms. In the second part we develop DC programming and DCA for solving some problems in finance. We begin with an introduction to the modern portfolio theory (The Chapter 3). The Chapter 4 is dedicated to the generalizations of the mean variance (MV) model of Markowitz, where we study the MV model under the buy-in threshold constraints, threshold constraints, and cardinality constraints. The Chapter 5 is devoted to the portfolio selection problem under downside risk measure and cardinality constraints. The Chapter 6 deals with the portfolio optimization under step increasing transaction costs functions. Finally, the robust investment strategies with discrete asset choice constraints are developed in the last chapter
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Reformat, Marek. "Application of genetic algorithms in control design for advanced static VAR compensator at ac/dc interconnection." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq23653.pdf.
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Rabbani, Ronak. "Developing and deploying enhanced algorithms to enable operational stability control systems with embedded high voltage DC links." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/12293.
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The increasing penetration of renewable energy resources within the Great Britain (GB) transmission system has created much greater variability of power flows within the transmission network. Consequently, modern transmission networks are presented with an ever increasing range of operating conditions. As a result, decision making in the Electricity National Control Centre (ENCC) of the GB electrical power transmission system is becoming more complex and control room actions are required for reducing timescales in the future so as to enable optimum operation of the system. To maximise utilisation of the electricity transmission system there is a requirement for fast transient and dynamic stability control. In this regard, GB electrical power transmissions system reinforcement using new technology, such as High Voltage Direct Current (HVDC) links and Thyristor-Controlled Series Compensation (TCSC), is planned to come into operation. The research aim of this PhD thesis is to fully investigate the effects of HVDC lines on power system small-disturbance stability in the presence of operational uncertainties. The main research outcome is the comprehensive probabilistic assessment of the stability improvements that can be achieved through the use of supplementary damping control when applied to HVDC systems. In this thesis, two control schemes for small-signal dynamic stability enhancement of an embedded HVDC link are proposed: Modal Linear Quadratic Gaussian (MLQG) controller and Model Predictive Controller (MPC). Following these studies, probabilistic methodologies are developed in order to test of the robustness of HVDC based damping controllers, which involves using classification techniques to identify possible mitigation options for power system operators. The Monte Carlo (MC) and Point Estimated Method (PEM) are developed in order to identify the statistical distributions of critical modes of a power system in the presence of uncertainties. In addition, eigenvalue sensitivity analysis is devised and demonstrated to ensure accurate results when the PEM is used with test systems. Finally, the concepts and techniques introduced in the thesis are combined to investigate robustness for the widely adopted MLQG controller and the recently introduced MPC, which are designed as the supplementary controls of an embedded HVDC link for damping inter-area oscillations. Power system controllers are designed using a linearised model of the system and tuned for a nominal operating point. The assumption is made that the system will be operating within an acceptable proximity range of its nominal operating condition and that the uncertainty created by changes within each operating point can possibly have an adverse effect on the controller’s performance.
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Bauer, Eric Charles. "Series Dc Arc Characterization, Prevention & Detection inAircraft Systems." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu154411083086475.
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Phan, Duy Nhat. "Algorithmes basés sur la programmation DC et DCA pour l’apprentissage avec la parcimonie et l’apprentissage stochastique en grande dimension." Thesis, Université de Lorraine, 2016. http://www.theses.fr/2016LORR0235/document.
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De nos jours, avec l'abondance croissante de données de très grande taille, les problèmes de classification de grande dimension ont été mis en évidence comme un challenge dans la communauté d'apprentissage automatique et ont beaucoup attiré l'attention des chercheurs dans le domaine. Au cours des dernières années, les techniques d'apprentissage avec la parcimonie et l'optimisation stochastique se sont prouvées être efficaces pour ce type de problèmes. Dans cette thèse, nous nous concentrons sur le développement des méthodes d'optimisation pour résoudre certaines classes de problèmes concernant ces deux sujets. Nos méthodes sont basées sur la programmation DC (Difference of Convex functions) et DCA (DC Algorithm) étant reconnues comme des outils puissants d'optimisation non convexe. La thèse est composée de trois parties. La première partie aborde le problème de la sélection des variables. La deuxième partie étudie le problème de la sélection de groupes de variables. La dernière partie de la thèse liée à l'apprentissage stochastique. Dans la première partie, nous commençons par la sélection des variables dans le problème discriminant de Fisher (Chapitre 2) et le problème de scoring optimal (Chapitre 3), qui sont les deux approches différentes pour la classification supervisée dans l'espace de grande dimension, dans lequel le nombre de variables est beaucoup plus grand que le nombre d'observations. Poursuivant cette étude, nous étudions la structure du problème d'estimation de matrice de covariance parcimonieuse et fournissons les quatre algorithmes appropriés basés sur la programmation DC et DCA (Chapitre 4). Deux applications en finance et en classification sont étudiées pour illustrer l'efficacité de nos méthodes. La deuxième partie étudie la L_p,0régularisation pour la sélection de groupes de variables (Chapitre 5). En utilisant une approximation DC de la L_p,0norme, nous prouvons que le problème approché, avec des paramètres appropriés, est équivalent au problème original. Considérant deux reformulations équivalentes du problème approché, nous développons différents algorithmes basés sur la programmation DC et DCA pour les résoudre. Comme applications, nous mettons en pratique nos méthodes pour la sélection de groupes de variables dans les problèmes de scoring optimal et d'estimation de multiples matrices de covariance. Dans la troisième partie de la thèse, nous introduisons un DCA stochastique pour des problèmes d'estimation des paramètres à grande échelle (Chapitre 6) dans lesquelles la fonction objectif est la somme d'une grande famille des fonctions non convexes. Comme une étude de cas, nous proposons un schéma DCA stochastique spécial pour le modèle loglinéaire incorporant des variables latentesThese days with the increasing abundance of data with high dimensionality, high dimensional classification problems have been highlighted as a challenge in machine learning community and have attracted a great deal of attention from researchers in the field. In recent years, sparse and stochastic learning techniques have been proven to be useful for this kind of problem. In this thesis, we focus on developing optimization approaches for solving some classes of optimization problems in these two topics. Our methods are based on DC (Difference of Convex functions) programming and DCA (DC Algorithms) which are wellknown as one of the most powerful tools in optimization. The thesis is composed of three parts. The first part tackles the issue of variable selection. The second part studies the problem of group variable selection. The final part of the thesis concerns the stochastic learning. In the first part, we start with the variable selection in the Fisher's discriminant problem (Chapter 2) and the optimal scoring problem (Chapter 3), which are two different approaches for the supervised classification in the high dimensional setting, in which the number of features is much larger than the number of observations. Continuing this study, we study the structure of the sparse covariance matrix estimation problem and propose four appropriate DCA based algorithms (Chapter 4). Two applications in finance and classification are conducted to illustrate the efficiency of our methods. The second part studies the L_p,0regularization for the group variable selection (Chapter 5). Using a DC approximation of the L_p,0norm, we indicate that the approximate problem is equivalent to the original problem with suitable parameters. Considering two equivalent reformulations of the approximate problem we develop DCA based algorithms to solve them. Regarding applications, we implement the proposed algorithms for group feature selection in optimal scoring problem and estimation problem of multiple covariance matrices. In the third part of the thesis, we introduce a stochastic DCA for large scale parameter estimation problems (Chapter 6) in which the objective function is a large sum of nonconvex components. As an application, we propose a special stochastic DCA for the loglinear model incorporating latent variables
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Régnier, Paul. "Effet des interactions homéostatiques entre cellules dendritiques, lymphocytes effecteurs et régulateurs sur les réponses immunitaires anti-tumorales : étude du rôle de différentes cellules dendritiques in vivo chez la souris, et étude algorithmique des relations complexes entre transcriptome tumoral, populations immunitaires et survie in silico chez les patients A paradoxical role for Flt3 ligand in tumor immune response reveals homeostatic control of NK and treg cells by dentritic cells Tumor infiltration by immune cells favors patient survival in some cancers bur is highly detrimental in immune-privileged sites." Thesis, Sorbonne Paris Cité, 2018. https://wo.app.u-paris.fr/cgi-bin/WebObjects/TheseWeb.woa/wa/show?t=2244&f=15657.
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Le cancer, l'une des principales causes de décès dans le monde, peut apparaître dans presque tout type de tissu, et est caractérisé par la prolifération anarchique de cellules et l'établissement d'une réponse immunitaire tolérogène favorisant la croissance tumorale, rendant souvent toute intervention médicamenteuse peu efficace. Les cellules dendritiques (DCs), véritables sentinelles de l'organisme, semblent jouer un rôle dans l'établissement à la fois d'une réponse anti-tumorale efficace et d'une tolérance face au cancer. Malgré tout, le rôle des différents sous-types de DCs dans le développement tumoral reste mal connu. Au cours de cette thèse, j'ai étudié différents acteurs cellulaires dendritiques et lymphocytaires, leurs relations et leur implication dans la réponse ou la tolérance immunitaire aux tumeurs. Durant la première partie de ma thèse, j'ai abordé l'effet de la modulation artificielle de l'homéostasie des DCs sur les autres cellules immunitaires ainsi que sur la réponse anti-tumorale in vivo chez la souris. J'ai montré qu'il existait un rôle paradoxal de la cytokine Flt3-L (FL) - un facteur de croissance essentiel à la différentiation et à l'homéostasie des DCs dites classiques/conventionnelles (cDCs) et des DCs plasmacytoïdes (pDCs) - sur la croissance du mélanome B16. En effet, sa surexpression ou son absence mènent à un meilleur contrôle du développement tumoral, accompagnées par une survie accrue des souris. L'absence de FL induit, en sus d'une disparition des cDCs et pDCs, une réduction drastique des lymphocytes T régulateurs (Tregs) protégeant la tumeur, ainsi qu'un renforcement général de la réponse immunitaire anti-tumorale adaptative via les lymphocytes T helpers. Sa surexpression induit une augmentation du nombre de cDCs et pDCs, et malgré une présence accrue de Tregs, un fort recrutement intra-tumoral de lymphocytes natural killer (NK) activés, un des acteurs majeurs de la réponse anti-tumorale innée. L'étude de souris déficientes en cDCs m'a également permis de démontrer l'existence d'un contrôle de l'homéostasie des NK par les DCs. De plus, la combinaison d'un traitement par FL et un anticorps déplétant les Tregs a un effet thérapeutique exacerbé chez la souris. Ensuite, par l'analyse bio-informatique de transcriptomes provenant de 35 types de cancers différents, j'ai montré que le paradoxe du FL existe également chez l'Homme, du moins pour certains cancers, et que les signatures géniques spécifiques de sous-populations de DCs peuvent être corrélées de manière paradoxale, bénéfique ou préjudiciable à la survie. En parallèle, j'ai évalué la présence de diverses cellules immunitaires dans l'infiltrat tumoral et leurs effets sur la survie des patients. Grâce aux algorithmes en langage R que j'ai développés, j'ai pu analyser pour tous les cancers étudiés les signatures géniques spécifiques de populations cellulaires immunitaires ainsi que les gènes et fonctions biologiques (pathways) les plus fortement dysrégulés ou impliqués dans le contrôle de la survie à 5 ans. Les résultats indiquent que les cellules immunitaires de l'infiltrat tumoral dans leur ensemble peuvent jouer, selon le cancer, un rôle bénéfique ou délétère. Cet infiltrat et les pathways immunitaires associés se sont révélés généralement de mauvais pronostic dans les cancers des organes dits immuno-privilégiés, mais en revanche bénéfiques dans les cancers du sein et de la peau. Pour chaque type de cancer, j'ai déterminé l'impact individuel sur la survie de différents types de cellules immunitaires et ai établi les corrélations entre les pathways impliqués et certaines de ces populations cellulaires. L'ensemble de ces résultats permet de mieux comprendre les relations complexes entre chaque cancer et son infiltrat cellulaire, et permettra à terme d'aider à développer des stratégies immuno-thérapeutiques plus adaptées à un environnement tumoral donné, en ciblant les populations immunitaires pouvant réellement impacter la survie des patientsThe cancer, one of the main causes of death in the world, can appear in almost any type of tissue, and is characterized by an anarchic proliferation of cells and the establishment of a tolerogenic immune response favouring the tumour growth, leading to low efficiency of drug interventions. Dendritic cells (DCs), real sentinels of the body, seem to play a role in the establishment of both efficient anti-tumoral immune response and tolerance against cancer. Nevertheless, the role of the different DCs subtypes in the tumoral development stays poorly known. During this thesis, I studied different dendritic and lymphocytic cellular actors, their relationships and their involvement in the immune response or tolerance to tumours. During the first part of my thesis, I studied the effect of the artificial modulation of DCs homeostasis on other immune cells and also on anti-tumoral response in vivo in mice. I proved the existence of a paradoxical role of the Flt3-L (FL) cytokine - a growth factor essential to the differentiation and the homeostasis of classical/conventional dendritic cells (cDCs) and plasmacytoid dendritic cells (pDCs) - on the B16 melanoma growth. In fact, its overexpression or absence both lead to a better control of the tumoral development, accompanied by an increased survival of mice. FL deficiency induces, together with the loss of both cDCs and pDCs, a drastic reduction of regulatory T lymphocytes (Tregs) protecting the tumour, and also a global reinforcement of the anti-tumoral adaptive immune response via helper T lymphocytes. Its overexpression induces an increase of the numbers of cDCs and pDCs, and despite a raised presence of Tregs, also a strong intra-tumoral recruitment of activated natural killer (NK) cells, one of the major actors of the anti-tumoral innate response. The study of cDCs-deficient mice allowed me to demonstrate the existence of a DCs-mediated control of the NK cells homeostasis. Furthermore, the combination of both FL treatment and antibody-mediated Tregs depletion has an exacerbated therapeutic effect in mice. Next, using bioinformatic analysis of transcriptomes of 35 different cancer types, I showed that the FL paradox also exists in humans, at least for some cancers, and that gene signatures specific of DCs subsets can be correlated in a paradoxical, beneficial or detrimental manner to survival. In parallel, I evaluated the presence of several immune cells in the tumour infiltrate and their effects on patients survival. Thanks to R language algorithms I developed, I was able to analyse for each studied cancer the immune cell populations-specific gene signatures and the most involved or dysregulated genes and biological functions (pathways) in the control of the 5 years survival of patients. My results indicate that the immune cells of the tumour infiltrate can play, according to the cancer, a beneficial or deleterious role. This immune infiltrate and the associated pathways were generally of bad prognosis in cancers of immune-privileged organs, but on the other hand were beneficial in skin and breast cancers. For each cancer type, I determined the individual impact on survival of several types of immune cells and established correlations between involved pathways and some of these cell populations. Altogether, the results allow to better understand the complex relationships between each cancer and the associated immune infiltrate, and will later lead to help the development of immunotherapeutic strategies more adapted to a given tumour environment, by targeting the immune populations that could really impact the survival of patients
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Samir, Sara. "Approches coopératives pour certaines classes de problèmes d'optimisation non convexe : Algorithmes parallèles / distribués et applications." Electronic Thesis or Diss., Université de Lorraine, 2020. http://www.theses.fr/2020LORR0039.
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Dans cette thèse, nous nous intéressons au développement des approches coopératives pour la résolution de certaines classes de problèmes d'optimisation non convexe qui jouent un rôle très important de par leurs applications dans de nombreux domaines. Il s'agit de combiner plusieurs algorithmes connus sous les noms des algorithmes composants (participants). La combinaison est basée principalement sur la programmation DC (Difference of Convex Functions) et DCA (DC Algorithm) avec des métaheuristiques. Pour la conception des logiciels nous utilisons les paradigmes de la programmation parallèle et distribuée. Chaque processus s'occupe d'un algorithme et communique avec les autres en appelant les fonctions de la bibliothèque MPI (Message Passing Interface) qui est un protocole de communication en programmation parallèle et distribuée. Outre l'introduction et la conclusion, la thèse est composée de quatre chapitres. Le chapitre 1 concerne les outils théoriques et algorithmiques comme servant de base méthodologique aux chapitres suivants. Le chapitre 2 s'articule autour les problèmes linéaires à variables mixtes binaires. Pour la résolution de ces problèmes, nous proposons une approche coopérative entre DCA et VNS (Variable Neighborhood Search). Puisque le schéma est constitué de deux algorithmes, nous optons pour la communication point à point entre les processus. Nous adaptons notre schéma pour résoudre le problème de localisation de l'installation avec des contraintes de capacités. Dans le chapitre 3, nous étudions la programmation quadratique à variables binaires. Nous développons une coopération entre DCA-Like (une nouvelle version de DCA) et deux autres métaheuristiques : GA (Genetic Algorithm) et MBO (Migrating Birds Optimization). Pour la communication entre les processus, nous utilisons la communication collective. Plus précisément une fonction qui permet la diffusion simultanée l'information d'un processus à tous les autres. Cette approche est adaptée et appliquée au problème d'affectation quadratique. Dans le chapitre 4, nous résolvons les problèmes de "clustering" via la minimisation de la somme des carrés par deux approches coopératives. La première consiste à combiner le DCA avec VNS et TS (Tabu Search). Quant à la deuxième, elle utilise la MBO avec les trois derniers algorithmes précités. Dans ces deux approches, nous utilisons une fonction de communication qui permet au processus d'accéder aux mémoires des autres et y enregistrer son information sans un temps d'attenteIn this thesis, we are interested in developing new cooperative approaches for solving some classes of nonconvex problems which play a very important role to model real-world problems. To design the schemes of our approaches, we combine several algorithms which we call the component (participant) algorithms. The combination is mainly based on DC (Difference of Convex Functions) and DCA (DC Algorithm) with metaheuristics. To develop our solution methods, we use the paradigm of parallel and distributed programming. Therefore, each process deals with an algorithm and communicates with the others by calling the functions of the MPI (Message Passing Interface) library which is a communication protocol in parallel and distributed programming. Besides the introduction and conclusion, this thesis is composed of four chapters. Chapter 1 concerns the theoretical and algorithmic tools serving as a methodological basis for the following chapters. Chapter 2 is about the mixed binary linear programs. To solve these problems, we propose a cooperative approach between DCA and VNS (Variable Neighborhood Search). Since the scheme is constituted by two algorithms, we use the point to point communication between the processes. As an application, we adapt our scheme to solve the capacitated facility location problem. Concerning chapter 3, we study the class of binary quadratic problems. Regarding the solution methods, we develop a cooperation between DCA-like which is a new version of DCA and two other metaheuristics: GA (Genetic Algorithm) and MBO (Migrating Birds Optimization). The exchange of information between the processes is expressed by using collective communication's function. More precisely, we call a function which allows broadcasting information of a process to all the others at the same time. This cooperative approach is adapted to the quadratic assignment problem. In chapter 4, we solve the MSSC (Minimum-Sum-of-Squares Clustering) using two cooperative approaches. The first combines DCA, VNS, and TS (Tabu Search). As for the second, it combines the MBO with the other three algorithms cited before. In these two approaches, we use a function of communication that allows a process to access the memories of the others and save the information there without blocking the work of the receiving processes
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Mohanty, Pranab. "Learning from biometric distances : performance and security related issues in face recognition systems." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002298.
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Bach, Tran. "Algorithmes avancés de DCA pour certaines classes de problèmes en apprentissage automatique du Big Data." Electronic Thesis or Diss., Université de Lorraine, 2019. http://www.theses.fr/2019LORR0255.
Full textAbstract:
De nos jours, le Big Data est devenu essentiel et omniprésent dans tous les domaines. Par conséquence, il est nécessaire de développer des techniques innovantes et efficaces pour traiter la croissance rapide du volume des masses de données. Nous considérons les problèmes suivants dans le contexte de Big Data : la sélection de groupes de variables pour la régression logistique multi-classes, la réduction de dimension par t-SNE (« t-distributed Stochastic Neighbor Embedding « en anglais) et l'apprentissage en profondeur pour la classification non-supervisée (« Deep Clustering « en anglais). Nous développons des algorithmes DC (Difference of Convex functions) avancés pour ces problèmes, qui sont basés sur la programmation DC et DCA (DC Algorithm) -- des outils puissants pour les problèmes d'optimisation non-convexes non-différentiables. Dans la première partie, nous étudions le problème de la sélection de groupes de variables pour la régression logistique multi-classes. Nous résolvons ce problème en utilisant des DCAs avancés – Stochastic DCA et DCA-Like. Plus précisément, Stochastic DCA se spécialise dans le problème de la minimisation de la grande somme des fonctions DC, et ne nécessite qu'un sous-ensemble de fonctions DC à chaque itération. DCA-Like relaxe la condition de convexité de la deuxième composante DC en assurant la convergence. Accelerated DCA-Like intègre la technique d'accélération de Nesterov dans DCA-Like pour améliorer sa performance. Les expériences numériques sur plusieurs jeux de données benchmark de grande taille montrent l'efficacité de tous les algorithmes proposés en termes de temps d'exécution et de qualité de la solution. La deuxième partie concerne t-SNE, une technique efficace de réduction de dimension non linéaire. t-SNE est modélisé sous forme d'un problème d'optimisation non-convexe. Motivés par le caractère novateur de DCA-Like et Accelerated DCA-Like, nous développons ces deux algorithmes pour résoudre le problème t-SNE. La supériorité de nos algorithmes, appliqués à la visualisation de données, par rapport aux méthodes existantes est illustrée via des expériences numériques réalisées sur les jeux de données de très grande taille. La troisième partie est consacrée à la classification non-supervisée par l'apprentissage en profondeur. Dans la première application, nous proposons deux algorithmes basés sur DCA pour combiner t-SNE avec MSSC (Minimum Sum-of-Squares Clustering) par ces deux approches : « tandem analysis » et joint-clustering. La deuxième application considère le clustering en utilisant l'auto-encodeur. Nous avons proposé une extension d'une classe d'algorithmes de joint-clustering pour résoudre le problème de mise à l'échelle de données (« scaling problem » en anglais), et appliqué pour un cas spécifique de joint-clustering avec MSSC. Les résultats numériques sur plusieurs jeux de données benchmark montre l'efficacité de notre algorithme comparé aux méthodes existantesBig Data has become gradually essential and ubiquitous in all aspects nowadays. Therefore, there is an urge to develop innovative and efficient techniques to deal with the rapid growth in the volume of data. This dissertation considers the following problems in Big Data: group variable selection in multi-class logistic regression, dimension reduction by t-SNE (t-distributed Stochastic Neighbor Embedding), and deep clustering. We develop advanced DCAs (Difference of Convex functions Algorithms) for these problems, which are based on DC Programming and DCA – the powerful tools for non-smooth non-convex optimization problems. Firstly, we consider the problem of group variable selection in multi-class logistic regression. We tackle this problem by using recently advanced DCAs -- Stochastic DCA and DCA-Like. Specifically, Stochastic DCA specializes in the large sum of DC functions minimization problem, which only requires a subset of DC functions at each iteration. DCA-Like relaxes the convexity condition of the second DC component while guaranteeing the convergence. Accelerated DCA-Like incorporates the Nesterov's acceleration technique into DCA-Like to improve its performance. The numerical experiments in benchmark high-dimensional datasets show the effectiveness of proposed algorithms in terms of running time and solution quality. The second part studies the t-SNE problem, an effective non-linear dimensional reduction technique. Motivated by the novelty of DCA-Like and Accelerated DCA-Like, we develop two algorithms for the t-SNE problem. The superiority of proposed algorithms in comparison with existing methods is illustrated through numerical experiments for visualization application. Finally, the third part considers the problem of deep clustering. In the first application, we propose two algorithms based on DCA to combine t-SNE with MSSC (Minimum Sum-of-Squares Clustering) by following two approaches: “tandem analysis” and joint-clustering. The second application considers clustering with auto-encoder (a well-known type of neural network). We propose an extension to a class of joint-clustering algorithms to overcome the scaling problem and applied for a specific case of joint-clustering with MSSC. Numerical experiments on several real-world datasets show the effectiveness of our methods in rapidity and clustering quality, compared to the state-of-the-art methods