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 251 for “"Gradient-based"”.
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Gradient-Based Distributed Model Predictive Control
… control (DMPC). One topic of the thesis is gradient-based optimization algorithms for solving the optimization problem arising in DMPC in a distributed manner. The underlying idea is to solve the optimization problem in distributed fashion using dual decomposition, which is a well-known …
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Gradient-Based Sensitivity Analysis with Kernels
… dimension reduction technique which uses the gradients of a function to determine important input directions. Unfortunately, we cannot expect to always have access to the gradients of our black-box functions. We thus begin by developing an estimator for the active subspace of a function using …
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Gradient-Based Optimum Aerodynamic Design Using Adjoint Methods
… to derive the adjoint system and the reduced gradient of the cost functional. The properties of adjoint variables at the sonic throat and the shock location are studied, revealing a logarithmic singularity at the sonic throat and continuity at the shock location. A numerical method, based on …
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Application of a gradient-based algorithm to structural optimization
… This study proposes the use of a robust gradient-based algorithm, whose adaptation to a variety of design problems is more straightforward. The algorithm was first applied to truss geometry and beam shape optimization, both forming part of the increasingly popular class of structural …
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Gradient-Based Surface Reconstruction and the Application to Wind Waves
New gradient-based surface reconstruction techniques are presented: regularized least absolute deviations based methods using common discrete differential operators, and spline based methods. All new methods are formulated in the same mathematical framework as convex optimization problems and can …
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Gradient-Based Surface Reconstruction and the Application to Wind Waves
New gradient-based surface reconstruction techniques are presented: regularized least absolute deviations based methods using common discrete differential operators, and spline based methods. All new methods are formulated in the same mathematical framework as convex optimization problems and can …
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Reacting plume inversion on urban geometries through gradient based design methodologies
… This work investigates a procedure built on gradient based design methods to allow for the solution of the so-called inverse chemistry problem in urban environments. The inverse chemistry problem consists of computing a release location based on the sensing of chemical byproducts of the …
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Parallel Computational Approach to Gradient Based EM Optimization of Microwave Structures
Electromagnetic (EM) based optimization and design closure is an essential part of RF and microwave design cycle. The main objective of this thesis is to develop a new gradient based EM optimization technique which exploits parallel computations. The proposed EM optimization technique achieves …
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Regular sensitivity calculation and gradient-based optimization of chaotic dynamical systems
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-12-01
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Dimensionally reduced modeling and gradient-based design of microchannel cooling networks
… in the microchannel networks. To capture the gradient discontinuity in the temperature field due to the microchannels, we employ the interface-enriched generalized finite element method (IGFEM) as the numerical solver, which greatly simplifies mesh generation by allowing for the use of meshes …
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Exploring Accumulated Gradient-Based Quantization and Compression for Deep Neural Networks
… We use the total accumulated absolute gradient over the training process as the indicator of importance of a parameter to the network. The most important parameters are quantized by the smallest amount. The post-training quantization method sorts and clusters the accumulated gradients …
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Gradient-based dimension reduction for Bayesian inverse problems and simulation-based inference
… differential equations and for simulation-based (likelihood-free) inference: in both settings, the high dimensionality of model parameters and/or data can render naïve posterior exploration intractable. We address this challenge by developing gradient-based methods that discover and exploit …
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Tetrahedral mesh optimization and generation via topological transformations and gradient based node perturbation
… both topological changes (i.e. flips) and gradient-based vertex optimization (i.e. smoothing) is demonstrated. This scheme is used in the optimization of tetrahedral meshes created by third-party software as well as a grid generation methodology created for this work. The particular …
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Optimization of an industrial centrifugal blower using gradient-free and gradient-based (adjoint) approaches
… Bien que les méthodes d’optimisation sans gradient soient couramment utilisées pour optimiser la forme aérodynamique des turbomachines, leur coût de calcul reste généralement élevé, notamment lorsqu’un grand nombre de variables de conception est impliqué. En revanche, la méthode adjointe, …
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Gradient-Based Optimization of ReaxFF Parameters Using Pytorch for the Study of Silica Precipitation
… speed up the process by utilizing the gradient of the potential. In this work, the gradient-based optimization of reactive force-field parameters using Pytorch was performed. We have implemented ReaxFF potential as a Pytorch model. The model’s performance was validated against existing …
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Permeability Distribution Estimation Based on Semi-Analytical Reservoir Simulator
… For our simulator, we considered both gradient based methods and non-gradient based methods. Gradient based algorithms have the big advantage of much faster convergence rate over non-gradient based algorithms. It is illustrated in this study that application of gradient based methods is …
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Hybrid And Hierarchical Image Registration Techniques
… classified into two categories: intensity-based and feature-based methods. The primary drawback of the intensity-based approaches is that it may fail unless the two images are misaligned by a moderate difference in scale, rotation, and translation. In addition, intensity-based methods lack …
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New model-based methods for non-differentiable optimization
Model-based optimization methods are effective for solving optimization problems with little structure, such as convexity and differentiability. Such algorithms iteratively find candidate solutions by generating samples from a parameterized probabilistic model on the solution space, and update the …
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Crashworthiness Multi-Material Topology Optimization for Minimum Mass
… derivatives required for conventional gradient-based structural optimization strategies. Non-gradient based methodologies for crashworthiness optimization exist in the literature which optimize structures via direct use of dynamic responses, but they are prohibitively computationally …
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Implementation and evaluation of a dual-sensor time-adaptive EM algorithm for signal enhancement
… recursive form. A more computationally efficient gradient-based parameter estimation step is also presented. The results of several experiments using synthetic data are shown. These experiments first illustrate that the algorithm works on data meeting all the assumptions made by the algorithm, …
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