Results 81 to 90 of about 192,768 (193)
We establish large sample approximations for an arbitray number of bilinear forms of the sample variance-covariance matrix of a high-dimensional vector time series using $ \ell_1$-bounded and small $\ell_2$-bounded weighting vectors.
Steland, Ansgar, von Sachs, Rainer
core +1 more source
The Kalman filter requires knowledge of the noise statistics; however, the noise covariances are generally unknown. Although this problem has a long history, reliable algorithms for their estimation are scant, and necessary and sufficient conditions for ...
Lingyi Zhang +5 more
doaj +1 more source
Estimation of Covariance Matrices under Sparsity Constraints
This paper is part of a discussion of the paper "Minimax Estimation of Large Covariance Matrices under L1-Norm" by Tony Cai and Harrison Zhou, to appear in Statistica ...
Rigollet, Philippe, Tsybakov, Alexandre
openaire +2 more sources
Accurate estimation of the state of charge (SOC) is essential for the safe and efficient operation of lithium-ion batteries. Conventional Adaptive Unscented Kalman Filter (AUKF) methods often exhibit limited accuracy, primarily due to the empirical ...
Hai Guo, Zhaohui Li, Haoze Xue, Jing Luo
doaj +1 more source
Direction of Arrival Estimation in Low-Grazing Angle: A Partial Spatial-Differencing Approach
This paper addresses a partial spatial-differencing (PSD) approach for the direction of arrival estimation in a low-grazing angle (LGA) condition. By dividing the sample covariance matrix into several column subvectors, we first form the corresponding ...
Junpeng Shi, Guoping Hu, Xiaofei Zhang
doaj +1 more source
The Cramer-Rao lower bound for the estimation of the affine transformation parameters in a multivariate heteroscedastic errors-in-variables model is derived.
Cohen, E. A. K., Kim, D., Ober, R. J.
core +1 more source
2D DOA estimator for coherently distributed sources using one snapshot
A two-dimensional (2D) direction-of-arrival (DOA) estimation method for coherently distributed (CD) sources has been proposed in high real-time situation using only one snapshot.
Qingqing Lin +3 more
doaj +1 more source
Positive Definite $\ell_1$ Penalized Estimation of Large Covariance Matrices [PDF]
The thresholding covariance estimator has nice asymptotic properties for estimating sparse large covariance matrices, but it often has negative eigenvalues when used in real data analysis.
Ma, Shiqian, Xue, Lingzhou, Zou, Hui
core
The evaluation of several climatological background-error covariance matrix (defined as the B matrix) estimation methods was performed using the ALADIN limited-area modeling data-assimilation system at a 4 km horizontal grid spacing.
Antonio Stanesic +2 more
doaj +1 more source
This paper presents a covariance matrix estimation method based on information geometry in a heterogeneous clutter. In particular, the problem of covariance estimation is reformulated as the computation of geometric median for covariance matrices ...
Xiaoqiang Hua +3 more
doaj +1 more source

