Results 31 to 40 of about 114,074 (272)
IEEE Access, 2019 Micro Doppler analysis of spin stabilized objects is of a great significance for attitude estimation and recognition of space targets. In practice, the radar cannot dwell on one target in a long interval continuously.
Ling Hong, Fengzhou Dai, Xili Wang
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Priors on the Variance in Sparse Bayesian Learning; the demi-Bayesian Lasso [PDF]
, 2008 We explore the use of proper priors for variance parameters of certain sparse Bayesian regression models. This leads to a connection between sparse Bayesian learning (SBL) models (Tipping, 2001) and the recently proposed Bayesian Lasso (Park and Casella,
Madigan, David
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IET Radar, Sonar & Navigation, 2022 The shallow water noise shows obvious impulsive property, which greatly degrades the direction of arrival (DOA) performance due to the conventional design concept based on the Gaussian assumption.
Xiao Feng +5 more
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Incremental Sparse Bayesian Ordinal Regression [PDF]
, 2018 Ordinal Regression (OR) aims to model the ordering information between different data categories, which is a crucial topic in multi-label learning. An important class of approaches to OR models the problem as a linear combination of basis functions that ...
de Rijke, Maarten, Li, Chang
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Iterative Reweighted Algorithms for Sparse Signal Recovery with Temporally Correlated Source Vectors [PDF]
, 2011 Iterative reweighted algorithms, as a class of algorithms for sparse signal recovery, have been found to have better performance than their non-reweighted counterparts.
Rao, Bhaskar D., Zhang, Zhilin
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EM-based parameter iterative approach for sparse Bayesian channel estimation of massive MIMO system
EURASIP Journal on Wireless Communications and Networking, 2017 One of the main challenges for a massive multi-input multi-output (MIMO) system is to obtain accurate channel state information despite the increasing number of antennas at the base station.
Sulin Mei, Yong Fang
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Leida xuebao, 2022 The direct position determination method based on compressed sensing depends on the accurate signal propagation model. With partially unknown propagation model parameters, its location performance will decline significantly.
Hongzhen YE +4 more
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Collaborative Deep Learning for Recommender Systems [PDF]
, 2015 Collaborative filtering (CF) is a successful approach commonly used by many recommender systems. Conventional CF-based methods use the ratings given to items by users as the sole source of information for learning to make recommendation.
Baldi P. +16 more
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Leida xuebao, 2016 Nowadays, high-speed sampling and transmission is a foremost challenge of radar system. In order to solve this problem, a compressive sensing approach is proposed for radar target signals in this study.
Zhong Jinrong, Wen Gongjian
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Deep Bayesian Gaussian processes for uncertainty estimation in electronic health records
Scientific Reports, 2021 One major impediment to the wider use of deep learning for clinical decision making is the difficulty of assigning a level of confidence to model predictions.
Yikuan Li +8 more
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