Results 41 to 50 of about 275,774 (266)
Feature extraction of vibration signal of roadheader based on singular value decompositio
In view of difficulty of dynamic load identification of roadheader, feature extraction method of vibration signal of roadheader based on singular value decomposition was proposed.
ZHANG Linfeng +5 more
doaj +1 more source
Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei +3 more
wiley +1 more source
Singular Value Decomposition [PDF]
While the eigenvalue decomposition \({\bf A} = \bf T{\bf \Lambda}T^{\prime},\) say, concerns only symmetric matrices, the singular value decomposition (SVD) \({\bf A} = \bf U{\bf \Delta}V^{\prime},\) say, concerns any n × m matrix. In this chapter we illustrate the usefulness of the SVD, particularly from the statistical point of view.
Simo Puntanen +2 more
openaire +2 more sources
Singular Value Decomposition and Ligand Binding Analysis
Singular values decomposition (SVD) is one of the most important computations in linear algebra because of its vast application for data analysis. It is particularly useful for resolving problems involving least-squares minimization, the determination of
André Luiz Galo +1 more
doaj +1 more source
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill +4 more
wiley +1 more source
A note on the singular value decomposition of (skew-)involutory and (skew-)coninvolutory matrices
The singular values $\sigma >1$ of an $n \times n$ involutory matrix $A$ appear in pairs $(\sigma, \frac{1}{\sigma}),$ while the singular values $\sigma = 1$ may appear in pairs $(1,1)$ or by themselves.
Faßbender, Heike, Halwaß, Martin
core +1 more source
Robust regularized singular value decomposition with application to mortality data [PDF]
We develop a robust regularized singular value decomposition (RobRSVD) method for analyzing two-way functional data. The research is motivated by the application of modeling human mortality as a smooth two-way function of age group and year.
Huang, Jianhua Z. +2 more
core +4 more sources
Multidimensional Profiling of MRI‐Negative Temporal Lobe Epilepsy Uncovers Distinct Phenotypes
ABSTRACT Objective Although hippocampal sclerosis (TLE‐HS) represents the most frequent cause of temporal lobe epilepsy (TLE), up to 30% of patients show no lesion on visual MRI inspection (TLE‐MRIneg). These cases pose diagnostic and therapeutic challenges and are underrepresented in surgical series.
Alice Ballerini +28 more
wiley +1 more source
This work introduces an adaptive human pilot model that captures pilot time‐delay effects in adaptive control systems. The model enables the prediction of pilot–controller interactions, facilitating safer integration and improved design of adaptive controllers for piloted applications.
Abdullah Habboush, Yildiray Yildiz
wiley +1 more source
Singular Value Decomposition Approaches in A Correspondence Analysis with The Use of R
The aim of a correspondence analysis is the graphical representation of the categories of variables in one frame of reference. This visualization is possible due to the decomposition of the basic matrix with the use of Singular Value Decomposition (SVD).
Brzezińska Justyna
doaj +1 more source

