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 20 of 11007 for “"sampling"”.
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Particle Thompson sampling
Thompson sampling is an effective Bayesian heuristic for solving stochastic bandit problems. But it is hard to implement in practice due to the intractability of maintaining a continuous posterior distribution. Particle Thompson sampling (PTS) is an approximation of Thompson sampling based on the …
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Nonuniform generalized sampling
… transform, so-called Nonuniform Generalized Sampling (NUGS). This framework is based on a recently introduced idea of generalized sampling for stable sampling and reconstruction in abstract Hilbert spaces, which allows one to tailor the reconstruction space to suit the function to be …
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DOUBLE SAMPLING FOR COARSE WOODY DEBRIS ESTIMATIONS FOLLOWING LINE INTERSECT SAMPLING
… carbon sequestration. Although many CWD sampling methods exist, accurate estimation is difficult and expensive. Double sampling incorporates auxiliary data that is positively correlated with the attribute of interest as a means of reducing sampling costs and/or increasing estimation …
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DOUBLE SAMPLING FOR COARSE WOODY DEBRIS ESTIMATIONS FOLLOWING LINE INTERSECT SAMPLING
… carbon sequestration. Although many CWD sampling methods exist, accurate estimation is difficult and expensive. Double sampling incorporates auxiliary data that is positively correlated with the attribute of interest as a means of reducing sampling costs and/or increasing estimation …
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Query-driven adaptive sampling
… a single approach for a broad range of adaptive sampling missions with risk and limited prior knowledge. To achieve this, we present contributions in planning adaptive missions in service of queries, and modeling multi-attribute environments. First, we define a query language suitable for …
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Network Sampling through Crawling
… important. We consider the problem of network sampling through crawling, in which the data collectors have no knowledge of the network of interest except the identity of a starting node. The data collector can expand the observed sample by querying an observed node. While the network science …
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Sampling From Stratified Spaces
… What information one should expect to get by sampling from a stratified space? In particular, this work explores relationships between geometry and different forms of CLT, namely classic, smeary and sticky. The work starts with explicit forms of CLTs for spaces of constant sectional curvature. …
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Sampling in Computational Cameras
… imaging by studying the intersection of sampling and artificial intelligence (AI). It has been demonstrated that AI shows superior performance in various image processing problems, ranging from super- resolution to classification. In this work we demonstrate that combining AI with …
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The Area Sampling Machine
… the shading at that sampled point. The sampling process can be thought of as a visibility test along the path of the ray having zero cross sectional area. Recent photorealistic image synthesis work has generally ignored the results from earlier visibility determination research. In the …
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Bayesian attributed network sampling
We address the problem of sampling in attributed networks. While uniform sampling is a task independent sampling method, in real-world, this is often difficult to implement as it requires random access to all the nodes of graph. Link tracing sampling methods such as random Walk, expansion sampling …
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Histogram sort with sampling
The student, - Vipul Harsh, submitted this Thesis for approval on 2017-07-04 at 08:53.
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Sampling Configurational Energy Landscapes
… which is a key limiting step in discrete path sampling. The efficiency of the transition state search is strongly dependent on the quality of the initial interpolation and so the alignment methods used. In this work two novel alignment algorithms are presented and benchmarked against existing …
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Sampling in human cognition
… The mind approximates Bayesian inference by sampling. Experiments across a wide range of cognition demonstrate Monte-Carlo-like behavior by human observers; moreover, models of cognition based on specific Monte Carlo algorithms can describe previously elusive cognitive phenomena such as …
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Discrete-time randomized sampling
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.
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Query-Driven Adaptive Sampling
… a single approach for a broad range of adaptive sampling missions with risk and limited prior knowledge. To achieve this, we present contributions in planning adaptive missions in service of queries, and modeling multi-attribute environments. First, we define a query language suitable for …
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Sampling time-resolved phenomena
… inverse problems and provide fundamental limits. Sampling theory, which deals with the interplay between the discrete and the continuous realms, plays a critical role in this work due to the continuous nature of physical world and the discrete nature of its proxy, that is, the time-resolved …
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Comparative particulate sampling methods
… most of these procedures is the long (24 hour) sampling times required, and the resultant insensitivity to fluctuations due to the long averaging intervals. The piezoelectric microbalance and high volume sampler techniques were employed in this investigation to measure the mass of ambient …
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Optimal and Permissible Sampling Rates for First-Order Sampling of Two-Band Signals
Sampling theory plays an essential role in the advancement of digital signal processing (DSP). All known DSP processors only work with digital samples of an analog signal (continuous-time signal). Therefore, reliable sampling of a signal is crucial for the successive phases of DSP. A well-known …
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Selecting expansion factor and number of sampling positions for point and plot sampling
… and expansion factor play in either sampling procedure. Validation of the estimated variances was done through a sampling simulation. Most of the variance approximations were considered unbiased and good in the estimation of their respective variances; only in plot samples with …
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