Results 81 to 90 of about 192,768 (193)

Asymptotics for high-dimensional covariance matrices and quadratic forms with applications to the trace functional and shrinkage

open access: yes, 2016
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

On the Identification of Noise Covariances and Adaptive Kalman Filtering: A New Look at a 50 Year-Old Problem

open access: yesIEEE Access, 2020
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

open access: yes, 2012
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

State of Charge Estimation Method for Lithium-Ion Batteries Based on Online Parameter Identification and QPSO-AUKF

open access: yesBatteries
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

open access: yesIEEE Access, 2017
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

Cramer-Rao Lower Bound for Point Based Image Registration with Heteroscedastic Error Model for Application in Single Molecule Microscopy

open access: yes, 2015
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

open access: yesThe Journal of Engineering, 2019
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]

open access: yes, 2012
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  

Comparison of NMC and Ensemble-Based Climatological Background-Error Covariances in an Operational Limited-Area Data Assimilation System

open access: yesAtmosphere, 2019
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

Information Geometry for Covariance Estimation in Heterogeneous Clutter with Total Bregman Divergence

open access: yesEntropy, 2018
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

Home - About - Disclaimer - Privacy