Essays about: "Bayesian Gaussian mixture models"
Showing result 1 - 5 of 6 essays containing the words Bayesian Gaussian mixture models.
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1. Multidimensional Classification of Radar Signals : A comparison between unidimensional and multidimensional classification models for pulsed radar signals
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Radar is a technique used by many different types of remote sensing systems to keep track of their surroundings. The transmitted radar signals may carry information that could be used to infer the type of transmitter. Multiple papers have investigated the classification of pulse repetition intervals produced by radar systems. READ MORE
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2. Out-of-distribution Recognition and Classification of Time-Series Pulsed Radar Signals
University essay from KTH/Matematisk statistikAbstract : This thesis investigates out-of-distribution recognition for time-series data of pulsedradar signals. The classifier is a naive Bayesian classifier based on Gaussian mixturemodels and Dirichlet process mixture models. READ MORE
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3. VePMAD: A Vehicular Platoon Management Anomaly Detection System : A Case Study of Car-following Mode, Middle Join and Exit Maneuvers
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Vehicle communication using sensors and wireless channels plays an important role to allow exchanging information. Adding more components to allow exchanging more information with infrastructure enhanced the capabilities of vehicles and enabled the rise of Cooperative Intelligent Transport Systems (C-ITS). READ MORE
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4. Particle-Based Online Bayesian Learning of Static Parameters with Application to Mixture Models
University essay from KTH/Matematisk statistikAbstract : This thesis investigates the possibility of using Sequential Monte Carlo methods (SMC) to create an online algorithm to infer properties from a dataset, such as unknown model parameters. Statistical inference from data streams tends to be difficult, and this is particularly the case for parametric models, which will be the focus of this paper. READ MORE
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5. Optimizing process parameters to increase the quality of the output in a separator : An application of Deep Kernel Learning in combination with the Basin-hopping optimizer
University essay from Linköpings universitet/Statistik och maskininlärningAbstract : Achieving optimal efficiency of production in the industrial sector is a process that is continuously under development. In several industrial installations separators, produced by Alfa Laval, may be found, and therefore it is of interest to make these separators operate more efficiently. READ MORE