Global ETD Search

41	Analýza vlivu velikosti okna a zpoždění na efektivitu TCP spojení / Analysis of the effect of delay and window size on TCP connection efficiency Kavický, Martin January 2010 (has links) Content of master’s thesis is description field of Sliding window and it’s expansion algorithms, witch are Slow start, Congestion avoidance, Fast Retransmit and Fast Recovery algorithm. Thereinafter is described creation of model in Opnet Modeler’s simulation area. In this simulation area was analyzed reactions of average transfer speed onto variance of data size, lost ratio, latency in short and long time slot and variance of receiver’s buffer size. In last section of this document is method design witch makes it possible of transfer speed control through the use of receiver’s buffer size dynamic setting.
42	Observation et commande d'une classe de systèmes non linéaires temps discret / Observation and control of a class of nonlinear discrete-time systems Gasmi, Noussaiba 14 November 2018 (has links) L’analyse et la synthèse des systèmes dynamiques ont connu un développement important au cours des dernières décennies comme l’atteste le nombre considérable des travaux publiés dans ce domaine, et continuent d’être un axe de recherche régulièrement exploré. Si la plupart des travaux concernent les systèmes linéaires et non linéaires temps continu, peu de résultats ont étaient établis dans le cas temps discret. Les travaux de cette thèse portent sur l’observation et la commande d’une classe de systèmes non linéaires à temps discret. Dans un premier temps, le problème de synthèse d’observateur d’état utilisant une fenêtre de mesures glissante est abordé. Des conditions de stabilité et de robustesse moins restrictives sont déduites. Deux classes de systèmes non linéaires à temps discret sont étudiées : les systèmes de type Lipschitz et les systèmes « one-sided Lipschitz ». Ensuite, une approche duale a été explorée afin de déduire une loi de commande stabilisante basée sur un observateur. Les conditions d’existence d’un observateur et d’un contrôleur stabilisant les systèmes étudiés sont formulées sous forme d’un problème d’optimisation LMI. L’efficacité et la validité des approches présentées sont montrées à travers des exemples académiques / The analysis and synthesis of dynamic systems has undergone significant development in recent decades, as illustrated by the considerable number of published works in this field, and continue to be a research theme regularly explored. While most of the existing work concerns linear and nonlinear continuous-time systems, few results have been established in the discrete-time case. This thesis deals with the observation and control of a class of nonlinear discrete-time systems. First, the problem of state observer synthesis using a sliding window of measurements is discussed. Non-restrictive stability and robustness conditions are deduced. Two classes of discrete time nonlinear systems are studied: Lipschitz systems and one-side Lipschitz systems. Then, a dual approach was explored to derive a stabilizing control law based on observer-based state feedback. The conditions for the existence of an observer and a controller stabilizing the studied classes of nonlinear systems are expressed in term of LMI. The effectiveness and validity of the proposed approaches are shown through numerical examples Systèmes à temps discret Systèmes Lipschitz Systèmes « one-sided Lipschitz » Optimisation LMI Stabilité au sens de Lyapunov Filtrage H∞ Approche avec fenêtre glissante Commande basée observateur Commande robuste Critère H∞ Incertitudes paramétriques Discrete-time systems Lipschitz systems One-sided Lipschitz systems LMI optimization Lyapunov Stability H∞ filtering Sliding window approach Observer-based control Robust control H∞ criterion Parametric uncertainties 620.001 185 003.83
43	Enabling Autonomous Operation of Micro Aerial Vehicles Through GPS to GPS-Denied Transitions Jackson, James Scott 11 November 2019 (has links) Micro aerial vehicles and other autonomous systems have the potential to truly transform life as we know it, however much of the potential of autonomous systems remains unrealized because reliable navigation is still an unsolved problem with significant challenges. This dissertation presents solutions to many aspects of autonomous navigation. First, it presents ROSflight, a software and hardware architure that allows for rapid prototyping and experimentation of autonomy algorithms on MAVs with lightweight, efficient flight control. Next, this dissertation presents improvments to the state-of-the-art in optimal control of quadrotors by utilizing the error-state formulation frequently utilized in state estimation. It is shown that performing optimal control directly over the error-state results in a vastly more computationally efficient system than competing methods while also dealing with the non-vector rotation components of the state in a principled way. In addition, real-time robust flight planning is considered with a method to navigate cluttered, potentially unknown scenarios with real-time obstacle avoidance. Robust state estimation is a critical component to reliable operation, and this dissertation focuses on improving the robustness of visual-inertial state estimation in a filtering framework by extending the state-of-the-art to include better modeling and sensor fusion. Further, this dissertation takes concepts from the visual-inertial estimation community and applies it to tightly-coupled GNSS, visual-inertial state estimation. This method is shown to demonstrate significantly more reliable state estimation than visual-inertial or GNSS-inertial state estimation alone in a hardware experiment through a GNSS-GNSS denied transition flying under a building and back out into open sky. Finally, this dissertation explores a novel method to combine measurements from multiple agents into a coherent map. Traditional approaches to this problem attempt to solve for the position of multiple agents at specific times in their trajectories. This dissertation instead attempts to solve this problem in a relative context, resulting in a much more robust approach that is able to handle much greater intial error than traditional approaches. GPS degradation GPS denied navigation state estimation observability error state sensor fusion vision-aided INS consistency multirotor micro air vehicle indoor flight outdoor flight pose graph optimization obstacle avoidance visual odometry Moving Horizon Estimation Pseudorange Linear Quadratic Regulator LQR Moving Horizon Estimation MHE Sliding Window Optimization Engineering
44	Neural basis and behavioral effects of dynamic resting state functional magnetic resonance imaging as defined by sliding window correlation and quasi-periodic patterns Thompson, Garth John 20 September 2013 (has links) While task-based functional magnetic resonance imaging (fMRI) has helped us understand the functional role of many regions in the human brain, many diseases and complex behaviors defy explanation. Alternatively, if no task is performed, the fMRI signal between distant, anatomically connected, brain regions is similar over time. These correlations in “resting state” fMRI have been strongly linked to behavior and disease. Previous work primarily calculated correlation in entire fMRI runs of six minutes or more, making understanding the neural underpinnings of these fluctuations difficult. Recently, coordinated dynamic activity on shorter time scales has been observed in resting state fMRI: correlation calculated in comparatively short sliding windows and quasi-periodic (periodic but not constantly active) spatiotemporal patterns. However, little relevance to behavior or underlying neural activity has been demonstrated. This dissertation addresses this problem, first by using 12.3 second windows to demonstrate a behavior-fMRI relationship previously only observed in entire fMRI runs. Second, simultaneous recording of fMRI and electrical signals from the brains of anesthetized rats is used to demonstrate that both types of dynamic activity have strong correlates in electrophysiology. Very slow neural signals correspond to the quasi-periodic patterns, supporting the idea that low-frequency activity organizes large scale information transfer in the brain. This work both validates the use of dynamic analysis of resting state fMRI, and provides a starting point for the investigation of the systemic basis of many neuropsychiatric diseases. fMRI Dynamic analysis Sliding window Sliding windows Resting state Default mode Functional connectivity Functional network Correlation Coherence Functional magnetic resonance imaging Local field potentials LFP Band-limited power BLP Inter-individual Intra-individual Spontaneous activity Brain Primary somatosensory cortex Rodent Rat Human Simultaneous experiments Neural basis Glial basis Neurons Astrocytes Vasomotion Hemodynamic response Dynamic Spatiotemporal dynamics Quasi-periodic patterns Brain networks Resting state networks Anesthesia Dexmedetomidine Isoflurane Awake Global signal Magnetic resonance imaging Brain Pathophysiology Brain mapping

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