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Showing 1 to 20 of 122 for “"SVD"”.
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Multiprocessor sparse SVD algorithms and applications
… 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 columns. On vector machines, …
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GDSVD: Scalable k-SVD via Gradient Descent
… rule for step-size selection provably finds k-SVD, i.e., the k ≥ 1 largest singular values and corresponding vectors, of any matrix, despite nonconvexity. There has been substantial progress towards this in the past few years where existing results are able to establish such guarantees for the …
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RANDOM PROJECTION AND SVD METHODS IN HYPERSPECTRAL IMAGING
Hyperspectral imaging provides researchers with abundant information with which to study the characteristics of objects in a scene. Processing the massive hyperspectral imagery datasets in a way that efficiently provides useful information becomes an important issue. In this thesis, we consider …
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CONVERGENGE ANALYSIS ON SVD-BASED ALGORITHMS FOR TENSOR LOW RANK APPROXIMATIONS
… that works to adjust one factor a time, proposed SVD-based algorithms improve two factors simultaneously. Convergence analysis both for the generalized Rayleigh quotient and the iterates themselves is the main contribution of this thesis. In addition, we also study the convergence property of a …
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Architectural, numerical and implementation issues in the VLSI design of an integrated CORDIC-SVD processor
… 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 six-chip custom VLSI chip set …
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Sporadic cerebral small vessel disease and cognitive abilities
Cerebral small vessel disease (SVD) is a leading cause of vascular cognitive impairment, contributing to multiple neurological disorders ranging from stroke, to mild cognitive impairment and dementia. However, despite a huge number of studies on the subject, we have a limited understanding of how …
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The role of cerebral small vessel disease in dementia
Introduction: Cerebral small vessel disease (SVD) is increasingly recognised as a key factor in dementia and cognitive impairment, although its role in the pathogenesis of Alzheimer’s disease (AD) remains poorly understood. Through the investigation of how SVD relates and interacts with (1) …
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Generating new data points using singular value decomposition
… 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 challenges faced during …
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Genetics of Cerebral Small Vessel Disease
Cerebral small vessel disease (SVD) is a leading cause of stroke and vascular dementia. The majority of cases are sporadic, occurring in the elderly hypertensive population. However, there also exist patients with familial disease. The most common form is Cerebral Autosomal Dominant Arteriopathy …
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Establishment of a Novel Patient hiPSC-derived in vitro Blood-Brain Barrier Model of Collagen IV Small Vessel Disease
Cerebral small vessel disease (SVD) is a prevalent cause of stroke (25-30%) and dementia (45%). Despite its frequency, little is known about the cause and disease progression of SVD. Matrisome alteration leading to blood-brain barrier (BBB) dysfunction is thought to play a role. Sporadic cases are …
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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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Disease mechanisms and markers of progression in cerebral small vessel disease
Introduction <br>Cerebral small vessel disease (SVD) is a common disease process accounting for a quarter of all ischaemic strokes, around 80% of haemorrhagic strokes, and is the major contributor to vascular cognitive impairment and dementia. Despite it being a major public health burden, …
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An Implementation-Based Exploration of HAPOD: Hierarchical Approximate Proper Orthogonal Decomposition
… vectors from the singular value decomposition (SVD) of an n-by-m "snapshot matrix" S, each column of which represents the computed state of the system at a given time. However, the direct computation of this decomposition can be computationally expensive, particularly for snapshot matrices that …
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Blood-Brain Barrier Permeability and Inflammation in Cerebral Small Vessel Disease
Introduction: Cerebral small vessel disease (SVD) is responsible for a third of strokes and is the most common cause of vascular dementia. It is characterised by white matter lesions and more diffuse damage outside of the lesions. Despite its importance, the mechanisms causing white matter damage …
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Fatigue in Cerebral Small Vessel Disease and its Relationship to Cognitive Behavioural Symptoms
Introduction <br>Cerebral Small Vessel Disease (SVD) is a disease affecting the small blood vessels in the brain. SVD is a leading cause of both stroke and vascular dementia, whilst cognitive behavioural symptoms such as fatigue are also frequent. Fatigue has a major impact on quality of life, yet …
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Evaluating Magnetic Resonance Imaging and Serum Markers As Surrogate Endpoints for Clinical Trials in Cerebral Small Vessel Disease
Cerebral small vessel disease (SVD) causes a quarter of all strokes and is the most common pathology underlying vascular cognitive impairment and dementia. White matter hyperintensities, lacunar infarcts, cerebral microbleeds and brain atrophy are characteristic features on conventional magnetic …
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Automated Brain Mapping to Evaluate the Relationship between Neurodegeneration, Cerebral Small Vessel Disease and Structural Covariance Network Disruption in Alzheimer's Disease
… contribution of cerebral small vessel disease (SVD) versus coexistent neurodegeneration to brain network disruption in AD. The first part of this thesis presents and validates a state-of-the-art automated hippocampal segmentation technique for magnetic resonance imaging to accurately measure …
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A Study of Wireless Modem Performance Using Multiple Element Antennas
… 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, e.g. incorrect channel …
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On the neurobiology of apathy and depression in cerebral small vessel disease
Cerebral small vessel disease (SVD) is a cerebrovascular pathology that affects the small vessels of the brain, resulting in heterogeneous brain tissue changes. These can lead to neuropsychiatric symptoms such as apathy, a loss of motivation, and depression, which is characterised by low mood and a …
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Multi-modality imaging assessment of cerebral small vessel disease biomarkers after stroke due to spontaneous intracerebral haemorrhage
… to result from cerebral small vessel diseases (SVDs). Cerebral amyloid angiopathy (CAA) and arteriolosclerosis (non-CAA SVD) are the two main types of SVD associated with ICH. The risk of recurrent ICH and post-stroke dementia may be higher with CAA-associated ICH compared with non-CAA …
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