Results 41 to 50 of about 150,538 (265)
Pauli decomposition via the fast Walsh-Hadamard transform
New Journal of PhysicsThe decomposition of a square matrix into a sum of Pauli strings is a classical pre-processing step required to realize many quantum algorithms. Such a decomposition requires significant computational resources for large matrices. We present an exact and
Timothy N Georges +3 more
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EURASIP Journal on Advances in Signal Processing, 2009 This paper considers the lower and upper bounds of eigenvalues of arrow-head matrices. We propose a parameterized decomposition of an arrowhead matrix which is a sum of a diagonal matrix and a special kind of arrowhead matrix whose eigenvalues can be ...
Bruce W. Suter, Lixin Shen
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Mueller Matrix Decomposition and Image for Non-Destructive Testing of UAVs Skin
Applied Sciences, 2023 Recently, Mueller matrix polarimetry (MMP) has been widely applied in many aspects, such as radar target decomposition, monitoring the glucose level, tissue diagnostics, biological samples, etc., but it is still challenging for the complex light–matter ...
Hongzhe Li +6 more
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FEBS Open Bio, EarlyView.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
Elevated Connectivity During Language Processing Is Associated With Cognitive Performance in SeLECTS
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Self‐Limited Epilepsy with Centrotemporal Spikes (SeLECTS) is associated with language impairments despite seizures originating in the motor cortex, suggesting aberrant cross‐network interactions. Here we tested whether functional connectivity in SeLECTS during language tasks predicts language performance.
Wendy Qi +8 more
wiley +1 more source
Bayesian Matrix Decomposition and Applications
CoRR, 2023 The sole aim of this book is to give a self-contained introduction to concepts and mathematical tools in Bayesian matrix decomposition in order to seamlessly introduce matrix decomposition techniques and their applications in subsequent sections. However, we clearly realize our inability to cover all the useful and interesting results concerning ...
openaire +2 more sources
Recommendation Algorithm Based on Coclus Joint Clustering and Non-negative Matrix Factorization [PDF]
Jisuanji gongcheng, 2019 Most of the current recommendation systems have many defects,such as low recommendation accuracy,being subject to sparsity and poor stability,so we propose a recommendation algorithm based on Coclus joint clustering and non-negative matrix decomposition ...
WANG Zehua, KE Xinsheng
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Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source
Split-and-Combine Singular Value Decomposition for Large-Scale Matrix
Journal of Applied Mathematics, 2013 The singular value decomposition (SVD) is a fundamental matrix decomposition in linear algebra. It is widely applied in many modern techniques, for example, high- dimensional data visualization, dimension reduction, data mining, latent semantic analysis,
Jengnan Tzeng
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Frontiers in Microbiology, 2023 Accumulating evidence has demonstrated various associations of long non-coding RNAs (lncRNAs) with human diseases, such as abnormal expression due to microbial influences that cause disease.
Lieqing Lin +6 more
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