Results 1 to 10 of about 401,989 (143)
Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems. [PDF]
Sensors (Basel), 2019 Hybrid massive MIMO structures with lower hardware complexity and power consumption have been considered as a potential candidate for millimeter wave (mmWave) communications. Channel covariance information can be used for designing transmitter precoders,
Hu R, Tong J, Xi J, Guo Q, Yu Y.
europepmc +4 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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Applied Sciences, 2022 A covariance matrix is an important parameter in many computational applications, such as quantitative trading. Recently, a global minimum variance portfolio received great attention due to its performance after the 2007–2008 financial crisis, and this ...
Tuan Tran, Nhat Nguyen, Trung Nguyen
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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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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
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The DOA Estimation Method for Low-Altitude Targets under the Background of Impulse Noise
Sensors, 2022 Due to the discontinuity of ocean waves and mountains, there are often multipath propagation effects and obvious pulse characteristics in low-altitude detection.
Bin Lin +4 more
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Covariance estimation via fiducial inference
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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IEEE Access, 2020 The estimation of the large and high-dimensional covariance matrix and precision matrix is a fundamental problem in modern multivariate analysis. It has been widely applied in economics, finance, biology, social networks and health sciences. However, the
Xin Yuan +3 more
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Covariance Estimation: The GLM and Regularization Perspectives [PDF]
, 2011 Finding an unconstrained and statistically interpretable reparameterization of a covariance matrix is still an open problem in statistics. Its solution is of central importance in covariance estimation, particularly in the recent high-dimensional data ...
Pourahmadi, Mohsen
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When do improved covariance matrix estimators enhance portfolio optimization? An empirical comparative study of nine estimators [PDF]
, 2010 The use of improved covariance matrix estimators as an alternative to the sample estimator is considered an important approach for enhancing portfolio optimization.
Lillo, Fabrizio +3 more
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