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 59 for “"Singular Value Decomposition (SVD)"”.
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Latent Semantic Indexing and Information Retrieval-A quest with BosSE
… Indexing (LSI) and an explanation of the Singular Value Decomposition (SVD) is given.
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A Study of Wireless Modem Performance Using Multiple Element Antennas
… Output (MIMO) systems. In such a case, the Singular Value Decomposition (SVD) of the channel matrix gives the optimal precoder and decoder. This thesis studies the performance of the SVD architecture under varying propagation environments, as well as its robustness to various impairments, …
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Distributed Singular Value Decomposition Through Least Squares
Singular value decomposition (SVD) is an essential matrix factorization technique that decomposes a matrix into singular values and corresponding singular vectors that form orthonormal bases. SVD has wide-ranging applications from principal component analysis (PCA) to matrix completion and …
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Modeling of short-distance running
… linear least squares estimation based on the Singular Value Decomposition (SVD) in order to estimate the two physiological parameters. Finally, we apply this computational model to real world data, first on a 1987 World Track record, and more extensively, on larger data sets consisting of …
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Investigating a Second-Order Optimization Strategy for Neural Networks
… and shows that an initialization using singular value decomposition (SVD) leads to drastically lower error values. Surprisingly, shallow but wide NNs, both in Transformer and CNN architectures, often perform better than their deeper counterparts. Overall, the research results recommend a …
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Architectural, numerical and implementation issues in the VLSI design of an integrated CORDIC-SVD processor
… the design of a systolic array for computing the Singular Value Decomposition (SVD) based on the Brent, Luk, Van Loan array. The use of COordinate Rotation DIgital Computer (CORDIC) arithmetic results in an efficient VLSI implementation of the processor that forms the basic unit of the array. A …
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Activity Recognition using Singular Value Decomposition
… a user's daily activities is of substantial value. It can be used to enhance medical monitoring by maintaining a diary that lists what a person was doing and for how long. The design of a wearable system to record context such as activity recognition is influenced by a combination of …
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An Examination into the Statistics of the Singular Vectors for the Multi-User MIMO Wireless Channel
… (MIMO) wireless channels make use of the singular value decomposition (SVD) of the channel matrix. For the multi-user case, the SVD of the channel matrix for each user may result in right and left singular vectors that are similar between users. This proposes another descriptive …
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Multiprocessor sparse SVD algorithms and applications
… develop four numerical methods for computing the singular value decomposition (SVD) of large sparse matrices on a multiprocessor architecture. We particularly consider the SVD of unstructured sparse matrices in which the number of rows may be substantially larger or smaller than the number of …
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Comparative Evaluation of Vorticity Transport Modeled Distortions and High-Fidelity ANSYS Solutions Using Modal Assurance Criterion
… Bulk Swirl, Twin Swirl, and Quad Swirl. Modal decomposition through singular value decomposition (SVD) is performed on the resulting in-plane velocity profiles for both the ROM and high-fidelity RANS simulations. The accuracy of the ROM is assessed through both conventional error analyses and a …
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Implementing a Tiled Singular Value Decomposition: A Framework for Tiled Linear Algebra in Julia
… through the implementation of tiled QR-based singular value decomposition (SVD), demonstrating how it streamlines the development process and accelerates scientific discovery. The developed framework is used to implement an in-GPU tiled SVD and an out-of-core GPU-accelerated SVD. Furthermore, …
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On the Use of Arnoldi and Golub-Kahan Bases to Solve Nonsymmetric Ill-Posed Inverse Problems
… such as spectral filtering methods use the singular value decomposition (SVD) and are effective at filtering inverted noise from solutions, but are computationally prohibitive on large problems. Hybrid methods apply regularization techniques to the smaller ``projected problem" that is …
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Using a non-modal method for system identification of highly damped and high modal density mechanical structures
… system identification method is based on the singular value decomposition (SVD) of the spatial mobility matrices that are acquired by the SLDV technique. Data reduction, filtering, periodization, and remapping techniques are applied to the measured data in the spatial domain. Linear and …
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In the Shadow of Prompts: Adversarial Attacks and Model Cloning in Large Language Models
… from the target model and analyzing them with singular value decomposition (SVD). Next, it trains smaller student models with varying transformer depths on publicly available data to reproduce the original model’s internal patterns and outputs. Experiments show that a 6-layer student can match …
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Azimuthal P-wave AVA Inversion for Fracture Orientation and Density
… approximation. Linear AVAZ inversions, based on singular value decomposition (SVD), and non-linear AVAZ inversion, based on generalized linear inversion (GLI), for fracture orientation and HTI anisotropy parameters, were applied on P-wave reflection coefficients with variable incident angle and …
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Alternating conditional expectation (ACE) applied to classification and recommendation problems
… Fundamentally, using known procedures such as Singular Value Decomposition (SVD) and Principal Component Analysis (PCA), dimension reduction for maximizing power can be achieved in a straight forward manner. Using the geometric framework, we relate calculation of SVD of a particular matrix …
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Messaging for large-scale distributed computation with factor graphs
… for hard problems, (b) Page-Rank, and (c) Singular Value Decomposition (SVD). We implement Factor Graph Computing on top of two different PubSub systems: Redis's out-of-the-box PubSub and a PubSub that we have built on top of the Ligra graph processing system[25]. Both of these offer single …
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Development of a Computationally Efficient Binaural Simulation for the Analysis of Structural Acoustic Data
… calculations required in this binaural analysis: singular value decomposition (SVD), and equivalent source reduction (ESR). The SVD method reduces the complexity of the HRTF computations by breaking the HRTFs into dominant singular values and vectors. The ESR method reduces the number of sources …
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On modelling volatility and mortality for pension schemes
… (CAE) model by proposing a modification of singular value decomposition (SVD) and principal component analysis (PCA) methods. Complementing this, a further study on mortality model by applying a range of multivariate DCC GARCH models in modelling the mortality dependence across multiple …
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Enhanced Recommender Systems by Biclustering
… items is either imputed or integrated into the singular value decomposition (SVD) framework without requiring any domain knowledge. Computationally, the BiRDS estimation avoids large matrices operation and memory storage, making it advantageous to attain scalability for massive datasets. …
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