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 10 of 10 for “"Stochastic Sampling"”.
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Optimal spectral reconstructions from deterministic and stochastic sampling geometries using compressive sensing and spectral statistical models
… number of Fourier samples using optimized, stochastic and deterministic sampling geometries. Two methodologies are developed: an optimal image reconstruction framework based on Compressive Sensing (CS) techniques and a new, Spectral Statistical approach based on the use of isotropic models …
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The accuracy of integrated star clusters parameters. The effects of stochasticity /
… inaccurate because the models do not take the stochastic sampling of star mass in clusters into account. A method to derive the parameters of unresolved star clusters by taking the stochastic sampling of star mass in clusters into account has been developed and shown to give more accurate …
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Integralinių žvaigždžių spiečių parametrų tikslumas. Stochastiniai efektai /
… inaccurate because the models do not take the stochastic sampling of star mass in clusters into account. A method to derive the parameters of unresolved star clusters by taking the stochastic sampling of star mass in clusters into account has been developed and shown to give more accurate …
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Bayesian Estimation for White Light Interferometry
… of the height estimate, obviating the need for stochastic sampling or simulation methods. In conventional surface estimation for white light interferometry, a primary height map is calculated pixel-wise from the raw data, followed by a postprocessing step where outliers and other measurement …
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Uncertainty and Generality of Transfer Learning Models in Predicting Signaling History
… for estimating uncertainty in IRIS predictions: stochastic sampling, Monte Carlo dropout, and ensemble prediction. These approaches were evaluated on two new endoderm and mesenchyme combinatorial perturbation screens. Across all methods, uncertainty values reliably reflected the varying …
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Tracking and modelling of team game interactions
… each player's movements. This thesis presents a stochastic sampling based multiple object tracker, capable of tracking objects from a single camera, in the complex domain of sports games. Sports players' shapes vary dramatically, presenting challenges to existing techniques. Multi-resolution …
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Structural Steel Reuse as a Cost-Effective Carbon Mitigation Strategy
… data analysis is then performed with both a stochastic sampling and nine real building projects to identify the variables most impacting carbon cost associated with reuse. Structural weight is found to have the greatest effect on reuse emissions, followed by number of elements, and then …
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Novel Hybrid Resampling Algorithms for Parallel/Distributed Particle Filters
… methods, use the Bayesian inference and the stochastic sampling technique to estimate the states of dynamic systems from given observations. Parallel/Distributed particle filters were introduced to improve the performance of sequential particle filters by using multiple processing units …
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Development and Application of Effective Stochastic Potential Method for Investigating Temperature-dependent Electronic Properties of Nanomaterials
… barrier, I have developed the Effective Stochastic Potential (ESP) method which addresses the challenge of conformational sampling. The ESP method is a first-principles technique which uses random matrix theory to treat noisy chemical environments of a system stochastically. In doing so, …
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Advancing RIS Optimization: From Ideal to Realistic Models
… maximization. The reformulation enables both stochastic and analytical interpretations of the original problems, as we demonstrate in our RIS applications. The former interpretation yields a stochastic sampling technique, whereas the latter yields an analytical GD approach using closed-form …