Results 131 to 140 of about 97,244 (184)

ODBAE: a high-performance model identifying complex phenotypes in high-dimensional biological datasets. [PDF]

Commun Biol
Shen Y, Zhang T, Liu Z, Kostelidou K, Xu Y, Yang L.   +5 more
europepmc   +1 more source

Dual-axis myelination covariance drives the functional connectivity emergence during infancy. [PDF]

Nat Commun
Liu W, Chen Y, Wang X, Fang T, Wang R, Cheng Y, Zhao X, Fan Q, Gao W, Ming D.   +9 more
europepmc   +1 more source

Optimal Sensor Placement in Buildings: Stationary Excitation. [PDF]

Sensors (Basel)
Ghahari F, Swensen D, Haddadi H.
europepmc   +1 more source

Kernel generalized least squares regression for network-structured data. [PDF]

PLoS One
Antonian E, Peters GW, Chantler M.
europepmc   +1 more source

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Augmented Covariance Matrix Reconstruction for DOA Estimation Using Difference Coarray

IEEE Transactions on Signal Processing, 2021
As is well known, nonuniform linear arrays have significant advantages in array aperture and degrees of freedom over uniform linear arrays. Using their difference coarrays, subspace-based approaches can be utilized to perform underdetermined and high-resolution direction-of-arrival (DOA) estimation.
Zhi Zheng, Wen-Qin Wang, Hing Cheung So
exaly   +2 more sources

Robust Adaptive Beamforming via Covariance Matrix Reconstruction Under Colored Noise

IEEE Signal Processing Letters, 2021
Aimed at the performance degradation of the standard Capon beamformer (SCB) when the signal of interest (SOI) appearing in the training data under the colored noise, a novel interference-plus-noise covariance matrix (INCM) reconstruction method is proposed in this letter.
Huichao Yang, Pengyu Wang, Zhongfu Ye
exaly   +2 more sources

Robust adaptive beamforming via subspace for interference covariance matrix reconstruction

Signal Processing, 2020
Abstract Adaptive beamforming may cause performance degradation when model mismatch errors exist. In this paper, we have developed subspace methods for robust adaptive beamforming (RAB). The two proposed methods utilize the orthogonality of subspace to reconstruct the interference covariance matrix (ICM).
Zhongfu Ye
exaly   +2 more sources

Average-intensity reconstruction and Wiener reconstruction of bioelectric current distribution based on its estimated covariance matrix

IEEE Transactions on Biomedical Engineering, 1995
This paper proposes two methods for reconstructing current distributions from biomagnetic measurements. Both of these methods are based on estimating the source-current covariance matrix from the measured-data covariance matrix. One method is the reconstruction of average current intensity distributions.
K, Sekihara, B, Scholz
exaly   +3 more sources