Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 6 of 6 for “"feedback particle filter"”.
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Feedback particle filter and its applications
The purpose of nonlinear filtering is to extract useful information from noisy sensor data. It finds applications in all disciplines of science and engineering, including tracking and navigation, traffic surveillance, financial engineering, neuroscience, biology, robotics, computer vision, weather …
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Comparison of two nonlinear filtering techniques - the extended Kalman filter and the feedback particle filter
… shown that importance sampling can be avoided in particle filter through an innovation structure inspired by traditional nonlinear filtering combined with optimal control and mean-field game formalisms. The resulting algorithm is referred to as feedback particle filter (FPF). The purpose of this …
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Comparison of nonlinear filtering techniques
… that importance sampling can be avoided in the particle filter through an innovation structure inspired by traditional nonlinear filtering combined with optimal control formalisms. The resulting algorithm is referred to as feedback particle filter. The purpose of this thesis is to provide a …
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Metrics for analytics and visualization of big data with applications to activity recognition
… sensor (accelerometer and gyroscope) data. A feedback particle filter (FPF) is implemented algorithmically to solve the estimation problem.
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Controlled particle systems for nonlinear filtering and global optimization
… and applications of controlled interacting particle systems for nonlinear filtering and global optimization problems. These problems are important in a number of engineering domains. In nonlinear filtering, there is a growing interest to develop geometric approaches for systems that evolve …
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Design and analysis of particle-based algorithms for nonlinear filtering and sampling
… is concerned with the design and analysis of particle-based algorithms for two problems: (i) the nonlinear filtering problem; (ii) and the problem of sampling from a target distribution. The contributions for these two problems appear in Part I and Part~II of the thesis. For the nonlinear …