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 9 of 9 for “"Iterative Estimation"”.
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Compound-Gaussian-regularized inverse problems: theory, algorithms, and neural networks
… such as the image prior distribution, into an iterative estimation algorithm, often, as an example, solving a regularized least squares problem. Instead, data-driven methods learn the inverse reconstruction mapping directly by training a neural network structure on actual signal and signal …
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Contributions to modeling and computer efficient estimation for Gaussian space -time processes
… to computer efficient methodology for estimation with space-time data. First we propose a parsimonious class of computer-efficient Gaussian spatial interaction models that includes as special cases CAR and SAR-like models. This extended class is capable of modeling smooth spatial random …
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Channel estimation and signal enhancement for DS-CDMA systems
… transceiver design, and S-T channel parameter estimation for direct-sequence code-division multiple-access (DS-CDMA) systems. Using the Bayesian framework, various linear and simplified nonlinear multiuser detectors are proposed, and their performances are analyzed. The simplified non-linear …
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Convex relaxation methods for graphical models : Lagrangian and maximum entropy approaches
… to the intractability of optimal inference and estimation over general graphs. In this thesis, we consider convex optimization methods to address two central problems that commonly arise for graphical models. First, we consider the problem of determining the most probable configuration-also …
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Learning with structured decision constraints
This thesis addresses several prediction and estimation problems under structured decision constraints. We consider them in two parts below. Part 1 focuses on supervised learning problems with constrained output spaces. We approach it in two ways. First, we consider an algorithmic framework that is …
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Energy-aware Sparse Sensing of Spatial-temporally Correlated Random Fields
… study the problem of energy efficient Level set estimation (LSE) of random fields correlated in time and/or space under a total power constraint. We consider uniform sampling schemes of a sensing system with a single sensor and a linear sensor network with sensors distributed uniformly on a line …
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Variance Change Point Detection under A Smoothly-changing Mean Trend with Application to Liver Procurement
… weighted least squares approach with an iterative estimation procedure that naturally integrates variance change point detection and smooth mean function estimation. Given the variance components, the mean function is estimated by smoothing splines as the minimizer of the penalized …
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Essays in political economy
… games, it also includes a chapter focusing on estimation of the U.S. legislators' ideal points in multiple meaningful dimensions. The first chapter presents a formal political competition model with differentiated candidates. In this model, the government expenditure must be financed through a …
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An Iterative Confidence Passing Approach for Parameter Estimation and Its Applications to MIMO Systems
This dissertation proposes an iterative confidence passing (ICP) approach for parameter estimation. The dissertation describes three different algorithms that follow from this ICP approach. These three variations of the ICP approach are applied to (a) macrodiversity and user cooperation diversity …