Results 51 to 60 of about 22,359,362 (203)
Estimating High Dimensional Covariance Matrices and its Applications [PDF]
Estimating covariance matrices is an important part of portfolio selection, risk management, and asset pricing. This paper reviews the recent development in estimating high dimensional covariance matrices, where the number of variables can be greater ...
Jushan Bai, Shuzhong Shi
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Advances in Mechanical Engineering, 2018 This article investigates a control precision analysis based on covariance analysis describing equation technique for the generic hypersonic vehicle attitude tracking system. For a nominal generic hypersonic vehicle attitude system, a global sliding mode
Jianguo Guo, Xinming Wang, Jun Zhou
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The hippocampal network model: A transdiagnostic metaconnectomic approach
NeuroImage: Clinical, 2018 Purpose: The hippocampus plays a central role in cognitive and affective processes and is commonly implicated in neurodegenerative diseases. Our study aimed to identify and describe a hippocampal network model (HNM) using trans-diagnostic MRI data from ...
Eithan Kotkowski +4 more
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Performance analysis of beamformers using generalized loading of the covariance matrix in the presence of random steering vector errors [PDF]
, 2005 Robust adaptive beamforming is a key issue in array applications where there exist uncertainties about the steering vector of interest. Diagonal loading is one of the most popular techniques to improve robustness.
Besson, Olivier, Vincent, François
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The affine equivariant sign covariance matrix: asymptotic behavior and efficiencies. [PDF]
We consider the affine equivariant sign covariance matrix (SCM) introduced by Visuri et al. (J. Statist. Plann. Inference 91 (2000) 557). The population SCM is shown to be proportional to the inverse of the regular covariance matrix. The eigenvectors and
Croux, Christophe, Ollila, E, Oja, H
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Acta Scientiarum. Agronomy, 2009 O feijoeiro é uma das principais culturas do país, e o Estado de Minas Gerais é um dos maiores produtores, representando cerca de 15% da produção nacional.
Maurício Martins +5 more
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E-Jurnal Matematika, 2013 Principal Component Regression is a method to overcome multicollinearity techniques by combining principal component analysis with regression analysis.
I PUTU EKA IRAWAN +2 more
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Analysis of Semi-Blind Channel Estimation in Multiuser Massive MIMO Systems With Perturbations
IEEE Access, 2019 In the massive multiple-input multiple-output (MIMO) systems, pilot contamination and signal perturbation are two important issues in the semi-blind channel estimation methods.
Cheng Hu, Hong Wang, Rongfang Song
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Finite Sample Analysis of Weighted Realized Covariance with Noisy Asynchronous Observations [PDF]
In this paper, we provide a framework to evaluate finite sample MSE of several realized covariance estimators when using nonsynchronous observations contaminated with microstructure noise. This framework enables us to examine different estimators.
Taro Kanatani
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Partial Differential Equations in Applied MathematicsCanonical correlation analysis (CCA) study the linear combinations between a two multivariate set of variable that have the maximum association among these two sets of variables. The main computation of the CCA is depend on the sample mean and covariance
Mufda Jameel Alrawashdeh +3 more
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