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.
Results
Showing 1 to 20 of 203 for “"singular value"”.
-
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 …
-
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 …
-
Generating new data points using singular value decomposition
… for small data sets. It introduces a Single Value Decomposition (SVD)-based model that draws inspiration from the ability of SVD to estimate a lower rank matrix. This approach seeks to overcome the limitations imposed by sample size constraints by expanding available data. Motivated by …
-
Curve characterization with high-order tensor singular value decomposition
Made available in DSpace on 2016-07-07T19:58:19Z (GMT). No. of bitstreams: 2 CAI-THESIS-2016.pdf: 2599852 bytes, checksum: c5150b52d2e0c26a7abcb48c71c76bf3 (MD5) LICENSE.txt: 4206 bytes, checksum: cd03b4878a87f39bc09a17838bd5b8de (MD5) Previous issue date: 2016-04-28
-
Finding analogies in semantic networks using the singular value decomposition
We present CROSSBRIDGE, an algorithm for finding analogies in large, sparse semantic networks. We treat analogies as comparisons between domains of knowledge. A domain is a small semantic network, i.e., a set of concepts and binary relations between concepts. We treat our knowledge base (the large …
-
A VLSI systolic array processor for complex singular value decomposition
The singular value decomposition is one example of a variety of more complex routines that are finding use in modern high performance signal processing systems. In the interest of achieving the maximum possible performance, a systolic array processor for computing the singular value decomposition …
-
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, …
-
Efficient reinforcement learning via singular value decomposition, end-to-end model-based methods and reward shaping
Reinforcement learning (RL) provides a general framework for data-driven decision making. However, the very same generality that makes this approach applicable to a wide range of problems is also responsible for its well-known inefficiencies. In this thesis, we consider different properties which …
-
Quantitative invertibility of random matrices : a combinatorial perspective
… the lower tail behavior of the least singular value of random matrices - a subject which has been intensely studied in the past two decades. Our focus is on obtaining high probability bounds, rather than on estimating the least singular value of a 'typical' realisation of the random …
-
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 …
-
An Iterative Method for Canonical Polyadic Decomposition of Tensors
<p>The Singular Value Decomposition (SVD) of matrices is widely used in least-squares regression, image and data processing, principal component analysis and many other applications. Often only the larger singular values of the matrix are needed to reconstruct the matrix and those below a given …
-
Exploration, processing and visualization of physiological signals from the ICU
… a novel method for data clustering based on the singular value decomposition and present some potential applications based on this method for use within the ICU setting.
-
Reconstruction de données satellitaires manquantes du lac Tanganyika
… d’une généralisation du théorème SVD (Singular Value Decomposition) des matrices aux tenseurs d’ordre trois. Les performances de ces deux algorithmes sont ensuite comparées sur les données satellitaires du lac Tanganyika fournies par Yves Cornet*, le but étant de reconstruire ces …
-
Latent Semantic Indexing and Information Retrieval-A quest with BosSE
… Indexing (LSI) and an explanation of the Singular Value Decomposition (SVD) is given.
-
Digital Tracking Control for Machine Tool Feed Drives
… cutting process model is used in a structured singular value based uncertainty analysis to predict the cutting conditions for which the machining process will remain stable. Experimental results from machining aluminum on a linear motor X-Y table validate this approach.
-
Uniqueness and Estimation of Three-Dimensional Motion Parameters of Rigid Objects
… parameters can be estimated by computing the singular value decomposition of a 3 x 3 matrix. The solution would be unique if three distinct frames are given. For the curved surface case, it is shown that seven point correspondences are sufficient to uniquely determine from two perspective …
Page 1 of 11