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 433 for “"subspace"”.
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Subspace estimation for subspace-based magnetic resonance spectroscopic imaging
This Thesis was approved for publication on 2016-04-15 at 14:08.
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Krylov subspace estimation
This thesis proposes a new iterative algorithm for the simultaneous computation of linear least-squares estimates and error variances. There exist many iterative methods for computing only estimates. However, most of these will not also compute error variances. A popular method for computing only …
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Krylov Subspace Methods with Fixed Memory Requirements: Nearly Hermitian Linear Systems and Subspace Recycling
Krylov subspace iterative methods provide an effective tool for reducing the solution of large linear systems to a size for which a direct solver may be applied. However, the problems of limited storage and speed are still a concern. Therefore, in this dissertation work, we present iterative Krylov …
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Subspace methods for portfolio design
… performance metric for financial investments. Subspace methods have been one of the pillars of functional analysis and signal processing. They are used for portfolio design, regression analysis and noise filtering in finance applications. Each subspace has its unique characteristics that may …
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Subspace identification via convex optimization
… to the classical problem of identifying a subspace from noisy measurements of a random process taking values in the subspace. We focus on the case where the measurement noise is component-wise independent, known as the factor analysis model in statistics. We develop a new analysis of an …
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A subspace optimizing data parallel complier
… A new approach to data parallel compilation, the Subspace compilation model, is introduced. This model is based on the idea that the shapes of data objects and how these shapes change represent higher-level performance considerations that the alignment of individual data elements. This model also …
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The E² Bathe subspace iteration method
Since its development in 1971, the Bathe subspace iteration method has been widely-used to solve the generalized symmetric-definite eigenvalue problem. The method is particularly useful for solving large eigenvalue problems when only a few of the least dominant eigenpairs are sought. In reference …
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Hamiltonian cycles in subset and subspace graphs.
… and the uniform-Hamiltonicity of subset graphs, subspace graphs, and their associated bipartite graphs. In 1995 paper "The Subset-Subspace Analogy," Kung states the subspace version of a conjecture. The study of this problem led to a more general class of graphs. Inspired by Clark and Ismail's …
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Krylov Subspace Methods in Power System Studies
… the use of numerical methods based on the Krylov subspace methodology on four areas of power systems: the power flow problem, the dynamic simulation, the trajectory sensitivity analysis and the model reduction. Krylov subspace techniques are tested and compared with traditional approaches. …
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Stationary Subspace Analysis: Towards understanding non-stationary data
… des ersten unüberwachten Verfahrens, Stationary Subspace Analysis (SSA), welches eine lineare Koordinatentransformation findet, die die beobachteten Daten in eine Gruppe von stationären und nicht-stationären Komponenten faktorisiert. Dies ist unerlässlich zur Analyse multivariater Daten, weil die …
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Estimation of Subspace Arrangements: Its Algebra and Statistics
… of polynomials vanishing on a union of subspaces; and statistically, we study how to estimate these polynomials robustly from real sample sets with noise and outliers. These new methods in many ways improve and generalize extant methods for modeling or clustering mixed data. Finally, we …
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Unified Discriminative Subspace Learning for Multimodality Image Analysis
… locally adaptive (QDLA) method and four new subspace learning algorithms corresponding to different learning-locality criteria are presented. These four algorithms are locally embedded analysis (LEA), discriminant simplex analysis (DSA), correlation embedding analysis (CEA), and correlation …
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Efficient invariant feature subspace recovery for domain generalization
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms
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Nearly tight oblivious subspace embeddings by trace inequalities
We present a new analysis of sparse oblivious subspace embeddings, based on the "matrix Chernoff" technique. These are probability distributions over (relatively) sparse matrices such that for any d-dimensional subspace of Rn, the norms of all vectors in the subspace are simultaneously …
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A channel subspace post-filtering approach to adaptive equalization
… do not exploit this structure. A channel subspace post-filtering algorithm that treats the least squares channel estimate as a noisy time series and exploits the channel correlation structure to reduce the channel estimation error is presented. The improvement in performance of the …
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Krylov Subspace Spectral Methods with Non-homogenous Boundary Conditions
<p>For this thesis, Krylov Subspace Spectral (KSS) methods, developed by Dr. James Lambers, will be used to solve a one-dimensional, heat equation with non-homogenous boundary conditions. While current methods such as Finite Difference are able to carry out these computations efficiently, their …
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Causality analysis advancements and applications by subspace-based techniques.
… the advanced time series analysis techniques. Subspace-based techniques adopted in this thesis include Singular Value Decomposition (SVD), Singular Spectrum Analysis (SSA) and Convergent CrossMapping (CCM). These subspace-based techniques have been proved powerful nonparametric time series …
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Krylov Subspace Methods for Topology Optimization on Adaptive Meshes
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.
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A subspace approach to accelerated cardiovascular magnetic resonance imaging
… arrhythmias. This dissertation describes a subspace approach to accelerate cardiovascular MRI, freeing cardiac MRI from gating techniques and enabling whole-heart 3D dynamic imaging for multiple simultaneous assessments. This imaging approach comprises developments in image modeling, data …
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Domain generalization for sequential data via invariant subspace recovery
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms
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