Results 301 to 310 of about 4,500,411 (350)

Variational Bayesian adaptation of process noise covariance matrix in Kalman filtering

Journal of the Franklin Institute, 2021
Adaptive Kalman filtering with unknown constant or varying process noise covariance matrix is studied. A resolution is proposed to directly estimate or tune the process noise covariance matrix in Kalman filtering using variational Bayesian technique.
G. Chang, Chao Chen, Qiuzhao Zhang, Shubi Zhang   +3 more
semanticscholar   +1 more source

Covariance Matrix Estimation

, 2016
Covariance matrix estimation allows the adaptation of Gaussian-based mutation operators to local solution space characteristics.
Oliver Kramer
semanticscholar   +2 more sources

Simplify Your Covariance Matrix Adaptation Evolution Strategy

IEEE Transactions on Evolutionary Computation, 2017
Bernhard Sendhoff, Hans-Georg Beyer
exaly   +2 more sources

Robust adaptive beamforming via subspace for interference covariance matrix reconstruction

Signal Processing, 2020
Adaptive beamforming may cause performance degradation when model mismatch errors exist. In this paper, we have developed subspace methods for robust adaptive beamforming (RAB).
Xingyu Zhu, Xu Xu, Zhongfu Ye
semanticscholar   +1 more source

Covariance Matrix Reconstruction for DOA Estimation in Hybrid Massive MIMO Systems

IEEE Wireless Communications Letters, 2020
Multiple signal classification (MUSIC) has been widely applied in wireless communications for direction-of-arrival (DOA) estimation. For massive multiple-input multiple-output (MIMO) systems operating at millimeter-wave bands, hybrid analog-digital ...
Si Li, Yinsheng Liu, Li You, Wenjin Wang, Hongtao Duan, Xu Li   +5 more
semanticscholar   +1 more source

Toeplitz Structured Covariance Matrix Estimation for Radar Applications

IEEE Signal Processing Letters, 2020
Following a geometric paradigm, the estimation of a Toeplitz structured covariance matrix is considered. The estimator minimizes the distance from the Sample Covariance Matrix (SCM) while complying with some specific constraints modeling the covariance ...
Xiao-Lin Du, A. Aubry, A. de Maio, G. Cui   +3 more
semanticscholar   +1 more source

The Covariance Matrix of the Information Matrix Test

Econometrica, 1984
In this note we point out how the covariance matrix of the information matrix test, due to \textit{H. White} [ibid. 50, 1-25 (1982; Zbl 0478.62088)], can be estimated without the computation of analytic third derivatives of the density function.
openaire   +2 more sources

Rank covariance matrix estimation of a partially known covariance matrix

Journal of Statistical Planning and Inference, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kuljus, Kristi, von Rosen, Dietrich
openaire   +1 more source

Estimation of the Covariance Matrix

2020
This 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
openaire   +1 more source

Shrinking the Covariance Matrix

The Journal of Portfolio Management, 2007
The subject here is construction of the covariance matrix for portfolio optimization. In terms of the ex post standard deviation of the global minimum-variance portfolio, there is no statistically significant gain in using more sophisticated shrinkage estimators rather than simpler portfolios of estimators.
David J. Disatnik, Simon Benninga
openaire   +1 more source