Results 71 to 80 of about 4,500,411 (350)
DOA-Estimation Method Based on Improved Spatial-Smoothing Technique
Mathematics, 2023 To improve the data utilization of the sensor array and direction-of-arrival-(DOA)-estimation performance for coherent signals, a DOA-estimation method with a modified spatial-smoothing technique is proposed. The covariance matrix of the received data of
Yujun Hou +4 more
doaj +1 more source
Bayes linear covariance matrix adjustment [PDF]
, 1995 In this thesis, a Bayes linear methodology for the adjustment of covariance matrices is presented and discussed. A geometric framework for quantifying uncertainties about covariance matrices is set up, and an inner-product for spaces of random matrices ...
Wilkinson, Darren James
core
Robust covariance estimation for data fusion from multiple sensors [PDF]
, 2011 This paper addresses the robust estimation of a covariance matrix to express uncertainty when fusing information from multiple sensors. This is a problem of interest in multiple domains and applications, namely, in robotics.
Lazarus, Samuel B. +5 more
core +1 more source
Comparative Effectiveness and Safety of Inebilizumab Versus Rituximab in AQP4‐IgG‐Positive NMOSD
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Rituximab (anti‐CD20, RTX) and inebilizumab (anti‐CD19, INE) represent B‐cell‐depleting therapies used for aquaporin‐4 antibody‐positive (AQP4‐IgG+) neuromyelitis optica spectrum disorder (NMOSD); however, direct comparative evidence remains limited.
Jie Lin +11 more
wiley +1 more source
Cholesky-based model averaging for covariance matrix estimation
Statistical Theory and Related Fields, 2017 Estimation of large covariance matrices is of great importance in multivariate analysis. The modified Cholesky decomposition is a commonly used technique in covariance matrix estimation given a specific order of variables.
Hao Zheng +3 more
doaj +1 more source
IEEE Access, 2019 Reconstructing the interference-plus-noise covariance matrix instead of searching for the optimal diagonal loading factor for the sample covariance matrix is a good method for calculating the adaptive beamforming coefficients.
Yuguan Hou +5 more
doaj +1 more source
Knowledge-aided Bayesian covariance matrix estimation in compound-Gaussian clutter [PDF]
, 2010 We address the problem of estimating a covariance matrix R using K samples zk whose covariance matrices are kR, where k are random variables. This problem naturally arises in radar applications in the case of compound-Gaussian clutter. In contrast to the
Bandiera, Francesco +6 more
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives Focal cortical dysplasia (FCD) is the most common etiology of drug‐resistant epilepsy in children. Focal to bilateral tonic–clonic seizures (FBTCS) mark a high risk of drug‐resistant epilepsy and involve thalamocortical circuitry in their generation and propagation.
Hua Xie +8 more
wiley +1 more source
An estimate of the inflation factor and analysis sensitivity in the ensemble Kalman filter [PDF]
Nonlinear Processes in Geophysics, 2017 The ensemble Kalman filter (EnKF) is a widely used ensemble-based assimilation method, which estimates the forecast error covariance matrix using a Monte Carlo approach that involves an ensemble of short-term forecasts.
G. Wu, G. Wu, X. Zheng
doaj +1 more source
Stage‐Dependent β‐Synuclein Links MRI and Cognitive Decline in Alzheimer's Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Synaptic degeneration drives cognitive decline in Alzheimer's disease (AD), but synaptic biomarkers are scarce. Brain‐enriched β‐synuclein emerged as a synaptic damage marker. We investigated its diagnostic, prognostic, and structural correlates across the AD continuum.
Ulaş Ay +15 more
wiley +1 more source