Results 91 to 100 of about 7,085,552 (171)
Adaptive variational sparse Bayesian estimation
, 2014 This paper presents an online version of the widely used sparse Bayesian learning (SBL) algorithm. Exploiting the variational Bayes framework, an efficient online SBL algorithm is constructed, that acts as a fully automatic learning method for the ...
Athanasios A. Rontogiannis +2 more
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Dianxin kexueTo address the channel estimation problem for non-orthogonal multiple access (NOMA) systems under non-Gaussian impulsive noise, a joint channel and impulsive noise estimation method based on approximate message passing was proposed, by exploiting the ...
LI Youming +3 more
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DOA estimation based on sparse Bayesian learning with moving synthetic virtual array
Electronics LettersIn scenarios with constrained physical aperture sizes, aiming to enhance the resolution and accuracy of Direction of Arrival (DOA) estimation, this paper proposes a novel approach that integrates a moving synthetic virtual array with Sparse Bayesian ...
Chao Zhu, Zhenmiao Deng
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Applied SciencesSparse Bayesian learning (SBL) is widely used for sound field reconstruction (SFR). Among various SBL approaches, pattern-coupled SBL has been demonstrated to achieve superior performance.
Simiao Chen +4 more
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Sparse Bayesian Learning-Based Channel Estimation for Fluid Antenna Systems [PDF]
Fluid antenna system (FAS) has emerged to give comparable performance to conventional multiple-input multiple-output (MIMO) systems with fewer radio-frequency (RF) chains.
Cui, Q, Tao, X, Wong, KK, Xu, B, Chen, Y
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Sparse Bayesian Learning Using Complex t-Prior for Beam-Domain Massive MIMO Channel Estimation
IEEE Open Journal of the Communications SocietyThis paper proposes a novel beam-domain channel estimation (CE) algorithm via sparse Bayesian learning (SBL) using complex t-prior for massive multi-user multiple-input multiple-output (MIMO) systems.
Kengo Furuta +2 more
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International Journal of Intelligent Systems and Applications in EngineeringReduced system complexity yields advantages that extend to enforcement obligations as well. The task of acquiring precise channel information for hybrid precoding in millimeter-wave (mmWave) systems is challenging for a multitude of reasons. Among the methods employed are analog precoding, a large number of antennas, and a pre-beamforming state with a ...
openaire +1 more source
IET Radar, Sonar & NavigationThe sparse Bayesian learning (SBL) algorithm has demonstrated its advantage in the direction of arrival (DOA) estimation. However, it requires a lot of computational cost to iteratively estimate the SBL hyperparameters from measurement data.
Xiang Pan +5 more
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System identification and interpretable modelling of dynamical systems with small data using sparse Bayesian learning [PDF]
Learning from data plays a major role in understanding complex natural and engineered systems. System identification (SysID), as a data-driven modelling technique, provides a powerful tool for building dynamical system models.
Wei, H.-L.
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Towards Inversion-Free Sparse Bayesian Learning: A Universal Approach
Sparse Bayesian Learning (SBL) has emerged as a powerful tool for sparse signal recovery, due to its superior performance. However, the practical implementation of SBL faces a significant computational complexity associated with matrix inversion. Despite
Li, Cheng +3 more
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