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 54 for “"approximation error"”.
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Markov Approximations: The Characterization of Undermodeling Errors
… a new perspective on different sources of errors to describe the impact of undermodeling. Our view is that modeling errors can be decomposed into two primary sources of errors: the approximation error and the estimation error. This thesis takes a first step towards exploring the …
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Error Visualization in Comparison of B-Spline Surfaces
… portion of the original surface. Typically, the approximation error in such cases is measured with a view to minimize it. The data associated with the error between two matching surfaces is large and needs to be filtered into meaningful information.This research looks at suitable norms for …
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Multilevel Summation for the Fast Evaluation of Forces for the Simulation of Biomolecules
… along with a precise operation count. The approximation error from the method is analyzed, with error bounds formulated in terms of the fundamental method parameters. The cost and error analyses enable the determination of optimal method parameters for a desired error tolerance. Various …
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Real-Time Detection of GPS Spoofing Attack with Hankel Matrix and Unwrapped Phase Angle Data
… attacks. Previous researchers exploited low-rank approximation of Hankel Matrix to differentiate between FDIA and physical events. We have demonstrated that, together with angle unwrapping algorithm, low-rank approximation of Hankel Matrix can help us separating GPS-spoofing attack with FDIA. The …
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Two-dimensional zero-phase FIR filter design with nonuniform frequency sampling
… desired filter frequency response such that the approximation error in the designed filter is reduced significantly and the shape performance is high. Three main types of two-dimensional zero-phase FIR filters that are most frequently used in practice have been considered: rectangular, circular, …
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An Interpolation-Based Approach to Optimal H<sub>∞</sub> Model Reduction
… approach, and give a method for finding the approximation to a state-space symmetric dynamical system which is optimal over a family of interpolants to the full order system. This family of interpolants has a simple parameterization that simplifies a direct search for the optimal interpolant. …
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Wavelet-Based Statistical Modeling and Image Estimation
… the TI wavelet transform from the viewpoints of approximation and estimation theory. First, we show that the TI expansion produces smaller approximation error when approximating smooth functions, and mitigates Gibbs artifacts when approximating discontinuous functions. Second, we study TI …
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Convergence of the Arnoldi Iteration for Estimating Extreme Eigenvalues
… the numerical range of a matrix. Prior bounds on approximation error often depend on eigenvalue gaps of the matrix, which lead to weaker bounds than observed in practice, specifically in applications where these gaps are small. Instead, we extend a line of work proving gap-independent bounds for …
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Application of non-uniform sampling techniques to digital filter synthesis
… technique in the synthesis. An analysis of the error function which measures the goodness in approximating a desired frequency response will also be undertaken. An algorithm which determines the optimal parameters.for a high pass filter will be developed and used to synthesize the particular …
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Digital Curvature Estimation: An Operator Theoretic Approach
… linear functions leads to a convexity preserving approximation that is crucial if additional sign changes in the curvature estimation have to be avoided. To this end, we will first establish the foundations of variation diminishing transforms and introduce the Bernstein and the Schoenberg operator …
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Probabilistic Approximations of Matrix Decompositions for Inverse Problems
… of computing the QR decomposition of sample approximations to matrices, and demonstrates applications of such factorisations to inverse problems. This thesis also makes use of probabilistic algorithms for constructing approximate matrix decompositions. A probabilistic method of constructing …
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Fully-coupled fluid-structure analysis of a baffled rectangular orthotropic plate using the boundary element and finite element methods
… is demonstrated which significantly reduces the approximation error. Storage requirements are reduced by grouping complex numbers. Finally the fully coupled fluid-structure interaction involving laminated composite plates is modeled using the combined FEM-BEM approach demonstrating the usefulness …
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Why deep neural networks for function approximation
… by a deep network for a given degree of function approximation. First, we consider univariate functions on a bounded interval and require a neural network to achieve an approximation error of ε uniformly over the interval. We show that shallow networks (i.e., networks whose depth does not depend …
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Recursive Bayesian Filtering Through a Mixture of Gaussian and Discrete Particles
… is heavily used due to low computational demand, approximation error is tied to their initialization, which causes difficulty during long term application. The latter circumvents this but at the cost of a significant increase in computation. An extremely popular stochastic filter termed the …
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Detecting exploit patterns from network packet streams
… provable bounds on resource consumption and approximation error. Our theoretical results are supported by experiments over real network traces and synthetic datasets.</p>
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Model reduction for Hidden Markov models
… upper bound on the stochastic L2 gain of the approximation error. The developed reduction procedure can be interpreted as an extension of the balanced truncation method to the broader class of Jump Linear Systems. In the Hidden Markov Model case, Hidden Markov Models are identified with …
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Geometric trimming of B-spline surfaces
… one. For this reason, a means to measure the error in approximating the original surface is implemented and this error is minimized. Trimming criteria is provided by mapping the trimming curves from the two-dimensional parametric space on to the three-dimensional B-spline surface. Since …
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Multi-modal and inertial sensor solutions for navigation-type factor graphs
… posteriors of all variables with minimal approximation error, while suppressing almost all lowlikelihood modes (in a non-permanent manner). Keeping with existing inertial navigation, we present a novel, continuous-time, retroactively calibrating inertial odometry residual function, using …
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Essays in Econometrics: Nonparametrics and Robustness
… discrete choice models that are robust to approximation error in the solution to the dynamic decision problem. Estimation and inference in dynamic discrete choice models often relies on approximation to lower the computational burden of dynamic programming. If it is not accounted for, the …
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EMG methods for prosthesis ankle-subtalar free-space control
… controllers calibration, and controllers’ linear approximation error are the most challenging problems among them. This thesis introduces three methods to solve those problems respectively. They are 1. A non-negative blind source separation algorithm named non-negative orthogonal …
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