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 134 for “"ill-posed"”.
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REGULARIZATION METHODS FOR ILL-POSED POISSON IMAGING
… the negative log-Poisson likelihood function is ill-posed, and hence some form of regularization is required. In this work, it involves solving a variational problem of the form u def = arg min u0 `(Au; z) + J(u); where ` is the negative-log of a Poisson likelihood functional, and J is a …
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REGULARIZATION METHODS FOR ILL-POSED POISSON IMAGING
… the negative log-Poisson likelihood function is ill-posed, and hence some form of regularization is required. In this work, it involves solving a variational problem of the form u def = arg min u0 `(Au; z) + J(u); where ` is the negative-log of a Poisson likelihood functional, and J is a …
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A Bayesian analysis of ill-posed problems
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.
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Improved estimation of Fourier coefficients for ill-posed inverse problems
<p>In this dissertation we present and solve an ill-posed inverse problem which involves reproducing a function f(x) or its Fourier coefficients from the observed values of the function. The observations of the f(x) are made at n equidistant points on the unit interval with p observations being …
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REGULARIZATION PARAMETER SELECTION METHODS FOR ILL POSED POISSON IMAGING PROBLEMS
… When the underlying model equation is ill-posed, regularization must be employed. I will present a computational framework for solving such problems, including statistically motivated methods for choosing the regularization parameter. Numerical examples will be included.
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REGULARIZATION PARAMETER SELECTION METHODS FOR ILL POSED POISSON IMAGING PROBLEMS
… When the underlying model equation is ill-posed, regularization must be employed. I will present a computational framework for solving such problems, including statistically motivated methods for choosing the regularization parameter. Numerical examples will be included.
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On existence, stability, accuracy and learning of approximate decoders for ill-posed inverse problems
… problems. Firstly, overly accurate AI methods will wrongly transfer details from one image to another reconstructed image creating a hallucination. Secondly, there is an accuracy-hallucination trade-off. Thirdly, there is an accuracy-stability trade-off, and optimising these trade-offs through …
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On the Use of Arnoldi and Golub-Kahan Bases to Solve Nonsymmetric Ill-Posed Inverse Problems
… linear systems of equations. In the context of ill-posed inverse problems, they tend to exhibit semiconvergence behavior making it difficult detect ``inverted noise" and stop iterations before solutions become contaminated. Regularization methods such as spectral filtering methods use the …
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Asymptotic theory for Bayesian nonparametric procedures in inverse problems
… inverse problems in both the mildly and severely ill-posed cases. This rate provides a quantitative measure of the quality of statistical estimation of the procedure. A theorem is proved in a general Hilbert space setting under approximation-theoretic assumptions on the prior. The result is …
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A bayesian approach to wireless location problems
… location estimation in wireless networks are proposed. We explore non-hierarchical and hierarchical Bayesian graphical models that use prior knowledge about physics of signal propagation, as well as different modifications of Bayesian bivariate spline models. The hierarchical Bayesian model that …
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Contributions to regularization theory and practice of certain nonlinear inverse problems
… considers Tikhonov regularization for nonlinear ill-posed operator equations in Hilbert scales with oversmoothing penalties. Sufficient as well as necessary conditions to establish convergence are introduced and convergence rate results are given for various parameter choice rules under a two …
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Row-Action Methods for Massive Inverse Problems
… a solution. Additionally, tools for regularizing ill-posed inverse problems are infeasible when the problem is too large. This thesis focuses on the development of row-action methods, which can be used to iteratively solve inverse problems when it is not possible to access the entire data-set or …
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Taming unstable inverse problems: Mathematical routes toward high-resolution medical imaging modalities
… that make the transition from some severely ill-posed parameter reconstruction problems to better-posed versions of them. The general introduction starts by defining what we mean by an inverse problem and its theoretical analysis. We then provide motivations that come from the field of …
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Robust Machine Learning Methods in Solving Inverse Problems
… problems are inherently challenging due to the ill-posed nature of IPs, where solutions are not unique and are sensitive to noise. Classical methods for solving inverse problems typically involve minimizing a least-squares data fidelity term combined with a handcrafted regularization function. …
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Blind Multichannel Image Deconvolution and Optimum Sparse Approximations
… applications, including regularization of ill-posed problems, design of digital filters with few non-zero coefficients and the computation of sparse approximate solutions to inverse problems. Because the problem is N-P complete, there exists a need to develop heuristic techniques that work …
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Learning image super resolution from joint examples
… priors are commonly learned to regularize the ill-posed SR problem, either using external LR-HR pairs or internal similar patterns repeating across di erent scales. We propose joint SR to adaptively combine the advantages of both external and internal SR. We de ne the two loss functions using …
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Advanced applications in wide-area impedance sensing
… Algorithms for image reconstruction from such ill-posed inverse problems are discussed and improvements are made. Hyperspectral techniques for extracting the occupancy values of various materials are shown. Finally, future experiments using this sensor for gesture sensing and as a purely …
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Recovery of 3D articulated motion from 2D correspondences
… 3D position from one 2D camera is an inherently ill-posed problem. This thesis focuses on recovery of 3D motion of an articulated model using 2D correspondences from an existing 2D tracker. A number of constraints are used to aid in reconstruction: (i) kinematic constraints from a 3D kinematic …
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