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 16 of 16 for “"Gauss-Newton method"”.
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Parallel Gauss-Newton method for CP decomposition
In this thesis, we formulate the Gauss-Newton algorithm to make it viable for running on distributed memory architectures and comparative to Alternating least squares algorithm for CP decomposition. Alternating least squares may exhibit slow or no convergence, especially when high accuracy is …
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Determination and interpretation of earthquake source locations in Sichuan Province, China
… earthquakes. To achieve these objectives, the Gauss-Newton method is applied iteratively to find the nonlinear least squares solution. The Monte Carlo method and the Gauss- Newton method were jointly used to locate events and simultaneously optimize the crust model. The iterative station …
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Co-processor offloading applied to passive coherent location with Doppler and bearing data
… differential correction (also known as the Gauss-Newton method) and uses Doppler and bearing data from a Passive Coherent Location (PCL) radar system. A PCL radar uses a network of receivers to track targets through their back-scatter from existing Continuous Wave (CW) transmissions, such as …
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Gauss-newton Based Learning For Fully Recurrent Neural Networks
… of RTRL is presented, that is based on the Gauss-Newton method. The method itself is an approximate Newton's method tailored to the specific optimization problem, (non-linear least squares), which aims to speed up the process of FRNN training. The new approach stands as a robust and …
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P- and S- wave tomography of the crust and uppermost mantle in China and surrounding areas
… are: 1) introducing the adaptive moving window method to obtain 2338 1D P and S models in China; 2) introducing a tomographic method to perform the 3D body wave travel-time tomography with the Moho discontinuity included. Both horizontal and vertical resolutions are highly controlled and smooth …
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Applications of low-rank approximation: complex networks and inverse problems
… with the aid of a regularized damped Gauss{Newton method. The inversion method is based on the low-rank approximation of the Jacobian of the function to be inverted.
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Joint Localization and Synchronization via User Cooperation in Non-Terrestrial Networks
… position estimate using TOA measurements and the Gauss-Newton method. Then, this coarse estimate is updated using the LevenbergMarquardt method which performs joint localization and synchronization. Finally, we derive a soft information-based filter that is used to continuously refine the position …
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Model parameter estimation of atherosclerotic plaque mechanical properties : calculus-based and heuristic algorithms
… was explored extensively and two solution methods are demonstrated. The first is a version of the traditional linear perturbation Gauss-Newton method, which contingent on an appropriate regularization scheme, was able to reconstruct both homogeneous and inhomogeneous distributions including …
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Optimization Based Domain Decomposition Methods for Linear and Nonlinear Problems
Optimization based domain decomposition methods for the solution of partial differential equations are considered. The crux of the method is a constrained minimization problem for which the objective functional measures the jump in the dependent variables across the common boundaries between …
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Seismic slope estimation: analyses in 2D/3D
… by noise, is difficult. The structure tensor method estimates slope from local structure within ellipsoids whose half-widths are specified by the user. This method performs well for seismic images with highly variable structure and computes slope fastest among three slope estimation methods …
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Numerical methods for optimization problems in water flow and reactive solute transport processes of xenobiotics in soils
… equations (ODEs). 2. ECOFIT: An efficient method for parameter estimation of xenobiotics in soils: The parameter estimation problem constrained by PDEs and ODEs is transformed by discretization into a large scale nonlinear constrained least-squares problem. Finite differences are employed …
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Topology Optimization Using Load Path and Homogenization
… and load transfer has been established. New methods for determining load paths in two dimensional structures, plates and shells are introduced. In the two-dimensional space, there are two load paths with their total derivative equal to the transferred load, their partial derivatives related …
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Numerical Methods for Parameter Estimation and Optimal Control of the Red River Network
In this thesis efficient numerical methods for the simulation, the parameter estimation, and the optimal control of the Red River system are presented. The model of the Red River system is based on the Saint-Venant equation system, which consists of two nonlinear first-order hyperbolic Partial …
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Learning and decentralized control in linear switched systems
… first part of the thesis, we develop synthesis methods for decentralized control of switched systems with mode-dependent (more generally, path-dependent) performance specifications. This specification flexibility is important when achievable system performance varies greatly between modes, as a …
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Numerical Methods for Separable Nonlinear Inverse Problems with Constraint and Low Rank
… reconstruction and deblurring require the use of methods to solve inverse problems. Since the problems are subject to many factors and noise, we can't simply apply general inversion methods. Furthermore in the problems of interest, the number of unknown variables is huge, and some may depend …
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Discontinuous Galerkin Based Multi-Domain Multi-Solver Technique for Efficient Multiscale Electromagnetic Modeling
<p>Discontinuous Galerkin (DG) methods provide an efficient option for modeling multiscale problems. With the help of the Riemann solver (upwind flux), a discontinuous Galerkin based multi-domain multi-solver technique is introduced in this work for multiscale electromagnetic modeling. …