Results 221 to 230 of about 114,074 (272)

Efficient Super-Resolution Bayesian Eletromagnetic Brain Imaging. [PDF]

IEEE Trans Biomed Eng
Cai C, Qi X, Yan J, Shang Y, Sekihara K, Wu W, Nagarajan SS.   +6 more
europepmc   +1 more source

Advanced channel estimation in OTFS and NOMA using deep bayesian gaussian processes and compressive sensing. [PDF]

Sci Rep
Anilkumar N, Sengan S.
europepmc   +1 more source

On the degrees of freedom of gridded control points in learning-based medical image registration. [PDF]

Med Phys
Yan W, Yang Q, Wang Y, Punwani S, Emberton M, Stavrinides V, Hu Y, Barratt D.   +7 more
europepmc   +1 more source

Improved bayesian network with graph attention and prior algorithm for aircraft engine fault root cause analysis. [PDF]

Sci Rep
Yuan L, Han G, Dong P.
europepmc   +1 more source

Sparse Bayesian learning with multiple dictionaries

Signal Processing, 2019
Abstract Sparse Bayesian learning (SBL) has emerged as a fast and competitive method to perform sparse processing. The SBL algorithm, which is developed using a Bayesian framework, iteratively solves a non-convex optimization problem using fixed point updates.
Santosh Nannuru, Kay L Gemba, Peter Gerstoft   +2 more
exaly   +4 more sources

Alternative to Extended Block Sparse Bayesian Learning and Its Relation to Pattern-Coupled Sparse Bayesian Learning [PDF]

IEEE Transactions on Signal Processing, 2018
We consider the problem of recovering block sparse signals with unknown block partition and propose a better alternative to the extended block sparse Bayesian learning (EBSBL). The underlying relationship between the proposed method EBSBL and pattern-coupled sparse Bayesian learning (PC-SBL) is explicitly revealed.
Lu Wang, Lifan Zhao, Susanto Rahardja
exaly   +7 more sources

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Sparse Bayesian learning for ranking

2009 IEEE International Conference on Granular Computing, 2009
In this paper, we propose a sparse Bayesian kernel approach to learn ranking function. In sparse Bayesian framework, a relevance determination prior over weights is used to automatic relevance determination. The inference techniques based on Laplace approximation is derived for model selection. By this approach accurate prediction models can be derived,
Xiao Chang, Qinghua Zheng
openaire   +1 more source

Sequential Sparse Bayesian Learning For Doa

2020 54th Asilomar Conference on Signals, Systems, and Computers, 2020
Sparse Bayesian learning (SBL) can effectively and accurately solve the direction-of-arrival (DOA) estimation problem. In this paper, we introduce a sequential SBL method for time-varying DOA estimation. Statistical information provided from previous time steps is modeled by a zero-mean multivariate Gaussian that is characterized by variance parameters.
Yongsung Park, Florian Meyer, Peter Gerstoft   +2 more
openaire   +1 more source