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Covariance Matrix Estimation Via Network Structure
SSRN Electronic Journal, 2016In this article, we employ a regression formulation to estimate the high dimensional covariance matrix for a given network structure. Using prior information contained in the network relationships, we model the covariance as a polynomial function of the symmetric adjacency matrix.
Wei Lan +3 more
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Large-scale Sparse Inverse Covariance Matrix Estimation
SIAM Journal on Scientific Computing, 2019A short summary of the mathematical problem of sparse inverse covariance estimation and its formulation as a convex optimization problem are given. \par The given topic is rather challenging. The proposed method for that problem is the QUIC method. The QUIC method is briefly reviewed after that.
Bollhöfer, Matthias +3 more
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Sparse Covariance Matrix Estimation by DCA-Based Algorithms
Neural Computation, 2017This letter proposes a novel approach using the [Formula: see text]-norm regularization for the sparse covariance matrix estimation (SCME) problem. The objective function of SCME problem is composed of a nonconvex part and the [Formula: see text] term, which is discontinuous and difficult to tackle.
Phan, Duy Nhat +2 more
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Distributed Sparse Covariance Matrix Estimation
2024 IEEE 13rd Sensor Array and Multichannel Signal Processing Workshop (SAM)Covariance matrix estimation is a crucial problem in many areas related to data analysis. While centralized sparse covariance matrix estimators have received extensive attention, practical considerations such as communication efficiency and privacy ...
Wenfu Xia, Ziping Zhao, Ying Sun
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Covariance Matrix Estimation for FDA-MIMO Adaptive Transmit Power Allocation
IEEE Transactions on Signal Processing, 2022Frequency diverse array multiple-input multiple-output (FDA-MIMO) radar produces an angle-range-dependent and time-varying transmit beampattern due to the small frequency increment across its array elements, which provides potential applications in new ...
Liu Wang, Wen-qin Wang, H. So
semanticscholar +1 more source
Toeplitz Structured Covariance Matrix Estimation for Radar Applications
IEEE Signal Processing Letters, 2020Following 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 ...
Xiaolin Du, A. Aubry, A. De Maio, G. Cui
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Improved Covariance Matrix Estimation With an Application in Portfolio Optimization
IEEE Signal Processing Letters, 2020One of the major challenges in multivariate analysis is the estimation of population covariance matrix from the sample covariance matrix (SCM). Most recent covariance matrix estimators use either shrinkage transformations or asymptotic results from ...
Samruddhi Deshmukh, Amartansh Dubey
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