Results 1 to 10 of about 534,560 (282)
Covariance estimation via fiducial inference [PDF]
Statistical Theory and Related Fields, 2021 As a classical problem, covariance estimation has drawn much attention from the statistical community for decades. Much work has been done under the frequentist and Bayesian frameworks.
W. Jenny Shi +3 more
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Accurate genetic and environmental covariance estimation with composite likelihood in genome-wide association studies. [PDF]
PLoS Genetics, 2021 Genetic and environmental covariances between pairs of complex traits are important quantitative measurements that characterize their shared genetic and environmental architectures.
Boran Gao, Can Yang, Jin Liu, Xiang Zhou
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Covariance Estimation in High Dimensions Via Kronecker Product Expansions [PDF]
IEEE Transactions on Signal Processing, 2013 This paper presents a new method for estimating high dimensional covariance matrices. The method, permuted rank-penalized least-squares (PRLS), is based on a Kronecker product series expansion of the true covariance matrix. Assuming an i.i.d.
Theodoros Tsiligkaridis, Alfred O Hero
exaly +3 more sources
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Accurate estimation of the clutter covariance matrix for the cell under test (CUT) is a committed step in the spatial-temporal adaptive processing (STAP) algorithm.
Tianfu Zhang +5 more
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Axioms, 2023 The generation of unprecedented amounts of data brings new challenges in data management, but also an opportunity to accelerate the identification of processes of multiple science disciplines.
Deniz Akdemir +2 more
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Actuators, 2023 In this paper, a novel state estimation approach based on the variational Bayesian adaptive Kalman filter (VBAKF) and road classification is proposed for a suspension system with time-varying and unknown noise covariance.
Qiangqiang Li, Zhiyong Chen, Wenku Shi
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2D-DOA Estimation in Switching UCA Using Deep Learning-Based Covariance Matrix Completion
Sensors, 2022 In this paper, we study the two-dimensional direction of arrival (2D-DOA) estimation problem in a switching uniform circular array (SUCA), which means performing 2D-DOA estimation with a reduction in the number of radio frequency (RF) chains.
Ruru Mei +3 more
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Ionospheric Kalman Filter Assimilation Based on Covariance Localization Technique
Remote Sensing, 2022 The data assimilation algorithm is a common algorithm in space weather research. Based on the GNSS data from the China Crustal Movement Observation Network (CMONOC) and the International Reference Ionospheric Model (IRI), a fast three-dimensional (3D ...
Jiandong Qiao +4 more
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IEEE Access, 2020 The prior covariance estimation method based on inverse covariance intersection (ICI) is proposed to apply the particle flow filter. The proposed method has better estimate performance and guarantees consistent estimation results compared with previous ...
Chang Ho Kang +2 more
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SPICE-ML Algorithm for Direction-of-Arrival Estimation
Sensors, 2019 Sparse iterative covariance-based estimation, an iterative direction-of-arrival approach based on covariance fitting criterion, can simultaneously estimate the angle and power of incident signal.
Yu Zheng, Lutao Liu, Xudong Yang
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