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 15 of 15 for “"Eigen-decomposition"”.
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Longitudinal principal components analysis for binary and continuous data
… component analysis (LPCA) using a random-effects eigen-decomposition, where the eigen-decomposition utilizes longitudinal information over time to model time-varying eigenvalues and eigenvectors of the corresponding covariance matrices. Our method can effectively analyze large marketing data …
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Spectral Regression: A Regression Framework for Efficient Regularized Subspace Learning
… These methods use information contained in the eigenvectors of a data affinity (\ie, item-item similarity) matrix to reveal the low dimensional structure in the high dimensional data. The most popular manifold learning algorithms include Locally Linear Embedding, ISOMAP, and Laplacian Eigenmap. …
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Adaptive transmit beamforming for simultaneous transmit and receive
… intensive matrix operations such as inversion or eigen-decomposition. This thesis ultimately provides, explains, and analyzes a viable method that can form a transmit-side null at the receiver and extract a weak signal of interest from the received signal while simultaneously transmitting another …
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Volumetric Attribute Compression for 3D Point Clouds using Feedforward Network with Geometric Attention
… B-spline bases spanning function spaces without eigen-decomposition. Feedforward network architecture means that the system is amenable to end-to-end neural learning. The key to our network is space-varying convolution, similar to a graph operator, whose weights are computed from the known 3D …
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Data analysis in proteomics novel computational strategies for modeling and interpreting complex mass spectrometry data
… full-scale proteomic analysis. Secondly, matrix decomposition and projection approaches are explored; these use an eigen-decomposition to extract general trends from groups of related spectra. A data visualization approach is demonstrated using these techniques, capable of visualizing trends in …
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DYADIC GREEN'S FUNCTIONS FOR LAYERED GENERAL ANISOTROPIC MEDIA AND THEIR APPLICATION TO RADIATION OF DIPOLE ANTENNAS
… solved.</p> <p>After a brief introduction, the eigenvector dyadic Green‟s functions (E-DGFs) for an unbounded general anisotropic medium through the eigen-decomposition method are derived. The E-DGFs of a layered anisotropic geometry are then constructed based on the derivation of the unbounded …
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Multiuser Multi Input Single Output (MU-MISO) Beamforming for 5G Wireless and Mobile Networks. A Road Map for Fast and Low Complexity User Selection, Beamforming Scheme Through a MU-MISO for 5G Wireless and Mobile Networks
… on channel inversion, and the other uses the Eigen decomposition that is derived subject to the signal to a leakage maximization problem. The two precoders show a degree of equivalency under certain assumptions for the number of antennas at the user end. The convex optimization of …
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Algorithms for passive dynamical modeling and passive circuit realizations
… schemes based on singular value or Hamiltonian eigenvalue perturbation, we are able to guarantee convergence to the optimal solution within the given relaxation. Compared to convex formulations based on direct Bounded-Real (or Positive-Real) Lemma constraints, we are able to reduce both memory …
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A complete reified temporal logic and its applications
… scenario graph matching problem, the traditional eigen-decomposition graph matching algorithm and the symmetric polynomial transform graph matching algorithm are critically examined and improved as two new algorithms named meta-basis graph matching algorithm and sort based graph matching algorithm …
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Design and performance of CDMA codes for multiuser communications
… using Karhunen-Loeve Transform (KLT) technique. Eigen decomposition technique is used to generate spread spectrum basis functions that are jointly spread in time and frequency domains for a given covariance matrix or power spectral density function. Since this is a closed form solution for …
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Energy loss and equilibration of a highly energetic parton in QCD plasmas
… the late time equilibration is studied using an eigen decomposition of the collision integral which is compared to the late time exponential decay. In the second analysis, we consider the evolution of the distribution in the longitudinal direction as well as in the polar angle with respect to the …
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ADVANCED STATISTICAL ANALYSIS FOR TAIL-END PROBABILITY PREDICTION AND PERFORMANCE RESPONSE CALCULATION OF SEMICONDUCTOR PACKAGING PRODUCTS WITH A LARGE NUMBER OF INPUT VARIABLES
… approximate integration-based approach, called eigenvector dimension reduction (EDR) method, for the UP analysis; (2) the stress-strength interference (SSI), and (3) the union of events. The proposed approach is capable of handling the number of input variables much larger than that has been …
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Deconvolution and sparsity based image restoration
… estimate is derived with single Eigen decomposition. Most of the dictionary learning algorithms confined the sparsity constraint to the sparse coding stage. In the second method, we look at the impact of enforcing the sparsity constraint also in the dictionary update stage. Within …
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Deconvolution and sparsity based image restoration
… estimate is derived with single Eigen decomposition. Most of the dictionary learning algorithms confined the sparsity constraint to the sparse coding stage. In the second method, we look at the impact of enforcing the sparsity constraint also in the dictionary update stage. Within …
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Semi-Supervised Learning for Scalable and Robust Visual Search
… including an orthogonal solution using eigen-decomposition, a revised strategy for learning non-orthogonal hash functions, a sequential learning algorithm to derive boosted hash functions, and an extension to unsupervised cases by using pseudo labels. Two parts of the thesis - bivariate …