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Covariance Matrix Estimation in Massive MIMO [PDF]
IEEE Signal Processing Letters, 2018 submitted to IEEE Signal Processing ...
David Neumann +2 more
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Estimation of the Covariance Matrix
2020This chapter addresses decision-theoretic estimation of an error covariance matrix in a multivariate linear model relative to a Stein-type entropy loss. With a unified treatment for high and low dimensions, some important improving methods of the best scale and the best triangular invariant estimators are discussed by using the residual sum of squares ...
Hisayuki Tsukuma, Tatsuya Kubokawa
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Methods of estimation of a covariance matrix
Computational Statistics and Data Analysis, 1987Douglas M Hawkins
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Kronecker Structured Covariance Matrix Estimation
2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07, 2007The estimation of signal covariance matrices is a crucial part of many signal processing algorithms. In some applications, the structure of the problem suggests that the underlying, true, covariance matrix is the Kronecker product of two matrices. Examples of such problems are channel modelling for MIMO communications and signal modelling of EEG data ...
Karl Werner +2 more
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On the calculation of a robustS-estimator of a covariance matrix
Statistics in Medicine, 1998An S-estimator of multivariate location and scale minimizes the determinant of the covariance matrix, subject to a constraint on the magnitudes of the corresponding Mahalanobis distances. The relationship between S-estimators and w-estimators of multivariate location and scale can be used to calculate robust estimates of covariance matrices.
Campbell, N.A. +2 more
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Improved estimation of the logarithm of the covariance matrix
2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012An improved estimator of certain bilinear forms of the logarithm of the covariance matrix is presented. The new estimator is shown to be consistent, not only for increasing sample size (as traditional estimators), but also when the observation dimension scales up at the same rate as the number of available observations.
Xavier Mestre +2 more
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Rank covariance matrix estimation of a partially known covariance matrix
Journal of Statistical Planning and Inference, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kuljus, Kristi, von Rosen, Dietrich
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Covariance Matrix Estimation in Complex Surveys
The Egyptian Statistical Journal, 1989Summary: An estimator of the asymptotic covariance matrix of the vector of second- order sample moments under cluster sampling design is derived by the Taylor expansion method. The form of the estimator under stratified cluster sampling design is obtained as well.
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