Results 11 to 20 of about 82,988 (261)
Weighted covariance matrix estimation [PDF]
Computational Statistics & Data Analysis, 2019 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Guangren Yang, Yiming Liu, Guangming Pan
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Estimating the covariance matrix: a new approach [PDF]
Journal of Multivariate Analysis, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tatsuya Kubokawa, M. S. Srivastava
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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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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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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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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 Matrix Estimation With Heterogeneous Samples
IEEE Transactions on Signal Processing, 2008 We consider the problem of estimating the covariance matrix Mp of an observation vector, using heterogeneous training samples, i.e., samples whose covariance matrices are not exactly Mp. More precisely, we assume that the training samples can be clustered into K groups, each one containing Lk, snapshots sharing the same covariance matrix Mk ...
Olivier Besson +2 more
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Covariance Matrix Estimation for Massive MIMO [PDF]
IEEE Signal Processing Letters, 2018 6 pages, 4 figures.
Vorobyov, Sergiy, A., Upadhya, Karthik
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Robust strong tracking unscented Kalman filter for non‐linear systems with unknown inputs
IET Signal Processing, 2022 This paper proposes a state estimation approach ‘robust strong tracking unscented Kalman filter with unknown inputs’ that can be applied to non‐linear systems with unknown inputs.
Xinghua Liu +5 more
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A subspace method for array covariance matrix estimation [PDF]
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), 2016 This paper introduces a subspace method for the estimation of an array covariance matrix. It is shown that when the received signals are uncorrelated, the true array covariance matrices lie in a specific subspace whose dimension is typically much smaller than the dimension of the full space.
Rahmani, Mostafa, Atia, George K.
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