An adaptive Singular Value Decomposition (SVD) algorithm is an optimal method to obtain spatial multiplexing gain MIMO-OFDM systems. We present an orthogonal reconstruction scheme to obtain more accurate SVD outputs and then the system performance will be greatly enhanced. Moreover this project reduces high cost of implementation and high decomposing latency. Finally adaptive SVD engine is simu...

The main contribution of this paper is to demonstrate that a new randomized SVD algorithm, proposed by Drineas et. al. in [4], is not only of theoretical interest but also a viable and fast alternative to traditional SVD algorithms in applications (e.g. image processing). This algorithm samples a constant number of rows (or columns) of the matrix, scales them appropriately to form a small matri...

In this paper, we propose a novel technique for video shot segmentation and classiication based on the Singular Value Decomposition (SVD). For the input video sequence, we create a feature-frame matrix A, and perform the SVD on it. From this SVD, we are able to not only derive the reened feature space to better segment the video sequence along time axis, but also deene metrics to enable classii...

Objective We explored the association between the total small vessel disease (SVD) score obtained with magnetic resonance imaging and risk factors and outcomes in the Japanese population. Methods The presence of SVD features, including lacunes, cerebral microbleeds, white matter changes, and basal ganglia perivascular spaces on MRI, was summed to obtain a "total SVD score" (range 0-4). Ordinal ...

BACKGROUND Cytokine gene variations are contributory factors in inflammatory pathology. Allele frequencies of interleukin (IL)-1 cluster genes [IL-1A(-889), IL-1B(-511), IL-1B(+3953), IL-1RN Intron 2 VNTR] and tissue necrosis factor (TNF)-alpha gene [TNFA(-308)] were measured in healthy blood donors (healthy control subjects), patients with angiographically normal coronary arteries (patient con...

Variational Mode Decomposition (VMD) is widely used for inspection purposes. The initial parameters are usually set manually, which a limitation of this technique. In paper, method to automatically select these through combination Singular Value (SVD) and Improved-VMD (IVMD) proposed. VMD applied multiple times with varying K-value parameter. original signal its sub-signals arising from decompo...

BACKGROUND Ligands of peroxisome-proliferator activated receptors (PPARs), such as non-esterified fatty acids (NEFAs), induce expression of angiopoietin-like protein 4 (ANGPTL4). Recently ANGPTL4 has been reported to be a mediator of intracellular adipose lipolysis induced by glucocorticoids. OBJECTIVE To determine the concentrations of ANGPTL4 in cord serum of neonates born by spontaneous va...

Cerebral small vessel disease (SVD) is a major contributor to stroke, and a leading cause of cognitive impairment and dementia. Despite the devastating effects of cerebral SVD, the pathogenesis of cerebral SVD is still not completely understood. Moreover, there are no specific pharmacological strategies for its prevention or treatment. Cerebral SVD is characterized by marked functional and stru...

Objective: All types of cerebral small vessel disease (SVD) markers including lacune, white matter hyperintensities (WMH), cerebral microbleeds, and perivascular spaces were found to be associated with poststroke depressive symptoms (PDS). This study explored whether the combination of the four markers constituting an overall SVD burden was associated with PDS. Methods: A cohort of 563 patients...

Every teacher of linear algebra should be familiar with the matrix singular value decomposition (or SVD). It has interesting and attractive algebraic properties, and conveys important geometrical and theoretical insights about linear transformations. The close connection between the SVD and the well known theory of diagonalization for symmetric matrices makes the topic immediately accessible to...