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Showing 1 to 20 of 50 for “"Variational methods"”.
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Variational Methods on Elastic Curves
<p>In this thesis we investigate elastic curves. These are curves with minimal bending energy as measured by the total squared curvature functional. We show that these can be computed by evolving curves in the direction of the negative gradient in certain Hilbert space settings. By discretizing the …
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Variational Methods in Ice Sheet Modelling
… that lead to these approximations. We develop a variational principle for Stokes flow, and neglect certain components in order to obtain the variational principle for the first-order approximation for ice flow. This result is fundamentally the result of assuming bed slopes to be much less than …
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Variational Methods in Ice Sheet Modelling
… that lead to these approximations. We develop a variational principle for Stokes flow, and neglect certain components in order to obtain the variational principle for the first-order approximation for ice flow. This result is fundamentally the result of assuming bed slopes to be much less than …
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Variational Methods for Nonlinear Partial Differential Equations
… of this work is to explain some basic aspects of variational methods for solving a class of nonlinear partial differential equations. First, relevant mathematical background of functional analysis and variational calculus is explained. One of the main results discussed is the existence theorem for …
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Scalable Gaussian process inference using variational methods
… is non-Gaussian. In this thesis, we study variational inference as a framework for meeting these challenges. An introductory chapter motivates the use of stochastic processes as priors, with a particular focus on Gaussian process modelling. A section on variational inference reviews the …
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Variational Methods for p-Laplacian Sturm-Liouville Problems
In this work we address the problem of eigencurves for the p-Laplacian operator on [0,1]. First we examine the simple case where p=2. Next, we prove the existence and several properties of the first eigencurve and its corresponding eigenfunction. In chapters 4 and 5, the nonhomogeneous case is …
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Estimation and variational methods for gradient algorithm generation.
Thesis. 1977. M.S.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
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Resonance Problems of the Fucik Spectrum Using Variational Methods
The Fucik spectrum of a linear operator, $L$, is defined to be the set,
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Variational Methods in the Firm's Financial Planning and Valuation
Made available in DSpace on 2014-12-11T23:19:52Z (GMT). No. of bitstreams: 1 7414528.pdf: 3025277 bytes, checksum: 8433b8720eb698db16a6409a751a8e65 (MD5) Previous issue date: 1974
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Variational methods for inference and estimation in graphical models
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1997.
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Scale independent piecewise smooth segmentation of images via variational methods
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1990.
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Medical Image Analysis Based on Graph Machine Learning and Variational Methods
… By leveraging various supervoxel creation methods such as VCCS, SLIC, Watershed, Meanshift, and Felzenszwalb-Huttenlocher, we structured 3D MRI images into a graph format. This format enabled the implementation of Spectral and Spatial GNNs to capture comprehensive local and global tumor …
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Numerical variational methods in differential geometry and applications to computer graphics
… geometry. These are incorporated into numerical methods for computer simulation of geometric objects. Some methods to generate geodesic curves on surfaces are discussed.
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Static two-dimensional calculation of the capacitance and impedance of open microstrip-like structures using variational methods
… and the other by Itoh and Hebert are based on variational methods. The results for the capacitance and impedance of a microstrip-like structure are calculated numerically and compared with measurements taken using a sample. The results presented in this thesis indicate that the first method …
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Characterizing Eigencurves for Differential Equations
This paper shows how variational methods may be used to describe an eigencurve
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Variational Approximation for Complex Regression Models
… flexible regression models and developing fast variational approximation methods for fitting them under a Bayesian framework. Models considered include mixtures of heteroscedastic regression models, mixtures of linear mixed models and generalized linear mixed models. The advantages of …
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Generalized approach to minimal uncertainty products
… states that saturate uncertainty products using variational methods is developed. Such a method allows one to numerically compute uncertainties in cases where the Robertson-Schrodinger (RS) uncertainty approach fails. To demonstrate the limitations of the RS approach, the ([Delta]x2 )([Delta]p) …
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Finite strip analysis of curved plate structures
… subject to normal loading. By applying variational methods to the principle of minimum potential energy the governing differential equation for a curved finite strip element is formed. The set of simultaneous differential equations resulting from a system of such strips are then solved …
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ΕΦΑΡΜΟΓΗ ΑΜΕΣΩΝ ΜΕΘΟΔΩΝ ΤΗΣ ΣΥΝΑΡΤΗΣΙΑΚΗΣ ΑΝΑΛΥΣΕΩΣ ΣΤΟΝ ΥΠΟΛΟΓΙΣΜΟ ΑΝΤΙΣΤΑΣΕΩΝ, ΑΥΤΕΠΑΓΩΓΩΝ ΚΑΙ ΧΩΡΗΤΙΚΟΤΗΤΩΝ
… THESIS IS DEALT WITH THE APPLICATION OF DIRECT VARIATIONAL METHODS (E.G. RAYLEIGH-RITZ METHOD, GALERKIN METHOD, KANTOROVICH METHOD) FOR THE CALCULATION OF RESISTANCE, INDUCTANCE AND CAPACITANCE. THE ESTIMATION OF INTERNAL INDUCTANCE OF HIGHLY PERMEABLE CONDUCTORS (M>>M) WITH VAROUS …
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Supercritical Semi-Linear Elliptic Problems Using Variational Principles
The thesis investigates the use of variational methods to study elliptic partial differential equations (PDEs) with supercritical nonlinearities. By focusing on convex subsets of a Banach space, the research overcomes compactness issues typically encountered with nonlinearities that exceed the …
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