Results 51 to 60 of about 924,331 (302)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingAccurate error covariance is crucial for postprocessing gravity recovery and climate experiment (GRACE) gravity field solutions in terms of spherical harmonic coefficients (SHCs).
Lin Zhang +3 more
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Patch-Based Principal Covariance Discriminative Learning for Image Set Classification
IEEE Access, 2017 Image set classification has attracted increasing attention with respect to the use of significant amounts of within-set information. The covariance matrix is a natural and effective descriptor for describing image sets. Non-singular covariance matrices,
Hengliang Tan, Ying Gao
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Physical properties of the Schur complement of local covariance matrices [PDF]
, 2007 General properties of global covariance matrices representing bipartite Gaussian states can be decomposed into properties of local covariance matrices and their Schur complements. We demonstrate that given a bipartite Gaussian state $\rho_{12}$ described
Eisert J Wolf M M +7 more
core +2 more sources
Comparing approximate methods for mock catalogues and covariance matrices II: power spectrum multipoles [PDF]
Monthly notices of the Royal Astronomical Society, 2018 We study the accuracy of several approximate methods for gravitational dynamics in terms of halo power spectrum multipoles and their estimated covariance matrix.
Linda Blot +21 more
semanticscholar +1 more source
Estimating Covariance Matrices
The Annals of Statistics, 1991 Let \(S_ 1\sim W_ p(\Sigma_ 1,n_ 1)\) and \(S_ 2\sim W_ p(\Sigma_ 2,n_ 2)\) be two independent \(p\times p\) Wishart matrices. It is desired to consider the minimax estimation of \((\Sigma_ 1,\Sigma_ 2)\) under the loss function \[ \sum_{i=1}^ 2\{\hbox {tr}(\Sigma_ i^{-1}\hat\Sigma_ i-\log| \Sigma_ i^{- 1}\hat\Sigma_ i|-p\}, \] extending known results ...
openaire +2 more sources
A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance
Sensors, 2018 The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system.
Binqi Zheng +3 more
doaj +1 more source
Journal of Mathematics, 2021 The explicit representation for the limiting spectral moments of sample covariance matrices generated by the periodic autoregressive model (PAR) is established.
Jin Zou, Dong Han
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Estimation for the Linear Model with Uncertain Covariance Matrices
, 2014 We derive a maximum a posteriori estimator for the linear observation model, where the signal and noise covariance matrices are both uncertain. The uncertainties are treated probabilistically by modeling the covariance matrices with prior inverse-Wishart
Bengtsson, Mats +4 more
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Two sample tests for high-dimensional covariance matrices [PDF]
, 2012 We propose two tests for the equality of covariance matrices between two high-dimensional populations. One test is on the whole variance--covariance matrices, and the other is on off-diagonal sub-matrices, which define the covariance between two ...
Chen, Song Xi, Li, Jun
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Performance of internal Covariance Estimators for Cosmic Shear Correlation Functions [PDF]
, 2015 Data re-sampling methods such as the delete-one jackknife are a common tool for estimating the covariance of large scale structure probes. In this paper we investigate the concepts of internal covariance estimation in the context of cosmic shear two ...
Eifler, T. F. +3 more
core +2 more sources