Results 31 to 40 of about 534,560 (282)
EURASIP Journal on Advances in Signal Processing, 2020 Due to the rapid development and wide application of compressed sensing and sparse reconstruction theory, there exists a series of sparsity-based methods for the antenna sensor array direction of arrival (DOA) estimation with excellent performance ...
Tao Chen, Lin Shi, Yongzhi Yu
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Frontiers in Applied Mathematics and Statistics, 2022 This work proposes a robust and non-Gaussian version of the shrinkage-based knowledge-aided EnKF implementation called Ensemble Time Local H∞ Filter Knowledge-Aided (EnTLHF-KA).
Santiago Lopez-Restrepo +9 more
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Efficient Estimation of Approximate Factor Models via Regularized Maximum Likelihood [PDF]
, 2012 We study the estimation of a high dimensional approximate factor model in the presence of both cross sectional dependence and heteroskedasticity. The classical method of principal components analysis (PCA) does not efficiently estimate the factor ...
Bai, Jushan, Liao, Yuan
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The DOA Estimation Method for Low-Altitude Targets under the Background of Impulse Noise
Sensors, 2022 Due to the discontinuity of ocean waves and mountains, there are often multipath propagation effects and obvious pulse characteristics in low-altitude detection.
Bin Lin +4 more
doaj +1 more source
Covariate assisted screening and estimation
The Annals of Statistics, 2014 Consider a linear model Y = Xβ + z, where X = Xn;p and z ≈ N(0; In). The vector β is unknown and it is of interest to separate its nonzero coordinates from the zero ones (i.e., variable selection). Motivated by examples in long-memory time series [11] and change point problem [2], we are primarily interested in the case where the Gram matrix G = X1X is
Ke, Zheng Tracy +2 more
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Generalized sparse covariance-based estimation [PDF]
Signal Processing, 2018 In this work, we extend the sparse iterative covariance-based estimator (SPICE), by generalizing the formulation to allow for different norm constraints on the signal and noise parameters in the covariance model. For a given norm, the resulting extended SPICE method enjoys the same benefits as the regular SPICE method, including being hyper-parameter ...
Swärd, Johan +2 more
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IEEE Access, 2021 In order to solve the problem that the gridless DOA estimation algorithms based on generalized finite rate of innovation (FRI) signal reconstruction model are not suitable for two-dimensional DOA estimation using planar array, a separable gridless DOA ...
Kunda Wang, Lin Shi, Tao Chen
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Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems [PDF]
, 2019 Hybrid massive MIMO structures with lower hardware complexity and power consumption have been considered as a potential candidate for millimeter wave (mmWave) communications. Channel covariance information can be used for designing transmitter precoders,
Guo, Qinghua +4 more
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Maximum Likelihood Estimation for Linear Gaussian Covariance Models [PDF]
, 2016 We study parameter estimation in linear Gaussian covariance models, which are $p$-dimensional Gaussian models with linear constraints on the covariance matrix.
Richards, Donald +2 more
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Variational Bayesian Parameter Estimation Techniques for the General Linear Model
Frontiers in Neuroscience, 2017 Variational Bayes (VB), variational maximum likelihood (VML), restricted maximum likelihood (ReML), and maximum likelihood (ML) are cornerstone parametric statistical estimation techniques in the analysis of functional neuroimaging data.
Ludger Starke +3 more
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