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Showing 1 to 20 of 251 for “"inverse problems"”.
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Inverse problems in thermoacoustics
… been relatively helpless in this subject is that problems of combustion instabilities involve physical and chemical matters that are still not well understood. Moreover, they exist in practical circumstances which are not readily approximated by models suitable to formulation within CFD. Hence, …
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Inverse problems in electromagnetics
Two inverse problems in electromagnetics are investigated in this thesis. The first is the retrieval of the effective constitutive parameters of metamaterials from the measurement of the reflection and the transmission coefficients. A robust method is proposed for the retrieval of metamaterials as …
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Approaches to Multiscale Inverse Problems
Many scientific problems involve parameters such as conductivity, permeability or density which vary on multiple spatial and/or temporal scales. When such a parameter is to be estimated from noisy indirect measurements we face a challenging dichotomy: In practical situations the computational cost …
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Parsimonious models for inverse problems
Made available in DSpace on 2020-03-02T22:10:20Z (GMT). No. of bitstreams: 2 PFISTER-DISSERTATION-2019.pdf: 5777487 bytes, checksum: a5face6e9622e2c59c29e773b9e91482 (MD5) LICENSE.txt: 4209 bytes, checksum: 25546ae0ab408cc4a6ef95982f2166f7 (MD5) Previous issue date: 2019-08-20
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Probabilistic solution of inverse problems
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1985.
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Inverse Problems in Structural Mechanics
… dissertation deals with the solution of three inverse problems in structural mechanics. The first one is load updating for finite element models (FEMs). A least squares fitting is used to identify the load parameters. The basic studies are made for geometrically linear and nonlinear FEMs of …
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PRACTICAL INVESTIGATIONS ON BAYESIAN INVERSE PROBLEMS
Inverse problems make up a challenging and practically important class of inference problems. Classical methods provide point estimates and confidence intervals which are asymptotically justified. As the computational power increased, however, ractitioners and researchers looked for better …
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A Multiplicative Regularisation for Inverse Problems
… Chapter 1 gives a general review of the field of inverse problems and common regularisation strategies, while Chapter 2 provides relevant technical details as mathematical preliminaries. The multiplicative regularisation model by Abubakar et al (2004) falls into the category of self-adaptive …
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Approximation errors in nonstationary inverse problems
Often, in nonstationary inverse problems, computing estimates with accurate high-dimensional models is not practically feasible. An approach called the Bayesian approximation error (BAE) has been shown to be able to handle highly approximate models. In the BAE approach, the approximation errors …
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Direct and inverse problems in machine learning
We analyze an inverse noisy regression model under random design with the aim of estimating the unknown target function based on a given set of data, drawn according to some unknown probability distribution. Our estimators are all constructed by kernel methods, which depend on a Reproducing Kernel …
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Novel optimisation methods for numerical inverse problems
Inverse problems involve the determination of one or more unknown quantities usually appearing in the mathematical formulation of a physical problem. These unknown quantities may be boundary heat flux, various source terms, thermal and material properties, boundary shape and size. Solving inverse …
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Structure-preserving machine learning for inverse problems
Inverse problems naturally arise in many scientific settings, and the study of these problems has been crucial in the development of important technologies such as medical imaging. In inverse problems, the goal is to estimate an underlying ground truth u∗, typically an image, from corresponding …
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Bayesian approaches to time-frequency inverse problems
… and its application to audio reconstruction problems. To address the inherent ambiguity of overcomplete dictionaries, the assumed generative mechanism of the audio waveform is enriched with prior structures that not only serve as a regularisation device but also reflect domain-specific …
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Instrumentation and algorithms for electrostatic inverse problems
This thesis describes tracking objects with low-level electric fields. A physical model is presented that describes the important interactions and the required mathematical inversions. Sophisticated hardware used to perform the measurements is described in detail. Finally, a discussion of the …
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Inverse problems in elliptic charged-particle beams
… approach to charged-particle dynamics problems involves extensive numerical optimization over the space of initial and boundary conditions in order to obtain desired charged-particle trajectories. The approach taken in the present work is to obtain analytic inverses wherever possible in …
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Row-Action Methods for Massive Inverse Problems
… applications have seen the rise of massive inverse problems, where there are too much data to implement an all-at-once strategy to compute a solution. Additionally, tools for regularizing ill-posed inverse problems are infeasible when the problem is too large. This thesis focuses on the …
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Computational Solution Of Inverse Problems With Simulated Annealing
The examination of inverse problems represents a fascinating, diverse and difficult area of study. Almost any problem in mathematics, physics and engineering has an associated inverse problem. The method of quasi-solutions allows one to reformulate inverse problems as a function minimization …
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Robust Machine Learning Methods in Solving Inverse Problems
Inverse problems (IPs) aim to recover a desired signal from noisy or corrupted measurements. These 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 …
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