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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Numerical Covariance Evaluation for Linear Structures Subject to Non-Stationary Random Inputs
ComputationRandom vibration analysis is a mathematical tool that offers great advantages in predicting the mechanical response of structural systems subjected to external dynamic loads whose nature is intrinsically stochastic, as in cases of sea waves, wind ...
M. Domaneschi +5 more
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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 Scale Analysis of Bivariate Non-Gaussian Time Series via Wavelet Cross-Covariance [PDF]
, 1998 this paper we study the scale analysis of bivariate time series through use of the wavelet cross-covariance. If
A. Serroukh +2 more
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Covariance-Based Sample Selection for Heterogeneous Data: Applications to Gene Expression and Autism Risk Gene Detection [PDF]
, 2020 Risk for autism can be influenced by genetic mutations in hundreds of genes. Based on findings showing that genes with highly correlated gene expressions are functionally interrelated, “guilt by association” methods such as DAWN have been developed to ...
Han Liu (288039) +2 more
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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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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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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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General covariance from the perspective of Noether's theorems [PDF]
, 2002 Analysis of Emmy Noether's 1918 theorems provides an illuminating method for testing the consequences of coordinate generality, and for exploring what else must be added to this requirement in order to give general covariance its far-reaching physical ...
Brading, Katherine +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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