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 7 of 7 for “"Gaussian Random Process"”.
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Boundary detection in ultrasonic speckle
… efficient. We show that when the underlying Gaussian random process underlying speckle noise is uncorrelated, a very simple suboptimal detection rule is nearly optimal, and that even in colored speckle, a related class of detectors can approach optimal performance. The basic technique is then …
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Krylov subspace estimation
… generation of a sample path of a given Gaussian random process and a low-rank approximation to the covariance matrix of a given process. The algorithm is compared to existing algorithms for realization in terms of an analytical estimate of computational cost and an experimental …
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Enhancing the bit error rate performance of ultra wideband systems using time-hopping pulse position modulation in multiple access environments
… interference is first assumed to be a zero mean Gaussian random process to simulate the scenario of a multi user environment. An exact BER calculation is then evaluated based on the characteristic function (CF) method, for Time Hopping-Pulse Position Modulation Ultra Wide Band (TH-PPM UWB) …
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Hyperspectral Image Acquisition and Calibration with Application to Skin Detection Systems
… of methods to enable accurate and reliable processing of hyperspectral images in the terrestrial setting. Unlike broadband trichromatic cameras, imaging spectrometers are inherently susceptible to chromatic aberration given their operational spectral range and narrowband resolution. We …
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Signal Detection and Modulation Classification in Non-Gaussian Noise Environments
… literature assume that the additive noise has a Gaussian distribution. However, while this is a good model for thermal noise, various studies have shown that the noise experienced in most radio channels, due to a variety of man-made and natural electromagnetic sources, is non-Gaussian and …
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Statistical Methods for Genetic Pathway-Based Data Analysis
… outcomes; the other is to propose a multilevel Gaussian graphical model for exploring both pathway and gene level network structures. For the first problem, we develop a semiparametric model via a Bayesian hierarchical framework. We model the pathway effect nonparametrically into a zero inflated …
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Some Advanced Model Selection Topics for Nonparametric/Semiparametric Models with High-Dimensional Data
Model and variable selection have attracted considerable attention in areas of application where datasets usually contain thousands of variables. Variable selection is a critical step to reduce the dimension of high dimensional data by eliminating irrelevant variables. The general objective of …