Results 141 to 150 of about 7,085,552 (171)

Structured noise champagne: an empirical Bayesian algorithm for electromagnetic brain imaging with structured noise. [PDF]

Front Hum Neurosci
Ghosh S, Cai C, Hashemi A, Gao Y, Haufe S, Sekihara K, Raj A, Nagarajan SS.   +7 more
europepmc   +1 more source

Off-grid hydroacoustic signal orientation estimation based on interpolation and subspace fitting in coprime arrays. [PDF]

PLoS One
Xing C, Tan G, Meng Q, Ran Y, Lu M.
europepmc   +1 more source

Comparative analysis of nanosilver toxicity in C. elegans: influence of exposure media on accumulation, physiological and biochemical effects. [PDF]

Environ Sci Pollut Res Int
Taipe Huisa AJ, Estrella Josende M, Michaelis V, Weishaupt AK, Gremme A, Lindenbeck LM, Slabon A, Lehmann CW, Dursun G, Altuncu MS, Delaittre G, Monserrat JM, Bornhorst J.   +12 more
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Robust interpolation of EEG/MEG sensor time-series via electromagnetic source imaging. [PDF]

J Neural Eng
Cai C, Qi X, Long Y, Zhang Z, Yan J, Kang H, Wu W, Nagarajan SS.   +7 more
europepmc   +1 more source

How forgiving are M/EEG inverse solutions to noise level misspecification? An excursion into the BSI-Zoo

Negi A, Haufe S, Gramfort A, Hashemi A.
europepmc   +1 more source

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Sparse Bayesian Learning (SBL)-Based Frequency-Selective Channel Estimation for Millimeter Wave Hybrid MIMO Systems

2019 National Conference on Communications (NCC), 2019
This work develops a novel sparse Bayesian learning (SBL)-based channel estimation technique for frequency-selective millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. Towards this end, the concatenated frequency-selective MIMO channel matrix is represented in terms of the beamspace channel vector employing suitable transmit and ...
Suraj Srivastava, Ch Suraj Kumar Patro, Aditya K. Jagannatham, Govind Sharma 0004   +3 more
openaire   +3 more sources

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

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).
Lu Wang, Lifan Zhao, Guoan Bi
exaly   +2 more sources

Details on O-SBL(MCMC): A Compressive Sensing Algorithm for Sparse Signal Recovery for the SMV/MMV Problem Using Sparse Bayesian Learning and Markov Chain Monte Carlo Inference [PDF]

, 2019
This report provides details on O-SBL(MCMC) algorithm for the recovery of jointly-sparse signals for the multiple measurement vector (MMV) problem.
Shekaramiz, Mohammad, Moon, Todd K, Gunther, Jacob H   +2 more
core   +3 more sources

Sparse Bayesian Learning With Multiple Dictionaries

Signal Processing, 2019
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. It
Kay L Gemba, Christoph Mecklenbräuker, Peter Gerstoft   +2 more
exaly   +2 more sources

FBC-SBL: Frequency Band Clustering Sparse Bayesian Learning for Off-Grid Wideband DOA Estimation With Different Frequency Bands

IEEE Geoscience and Remote Sensing Letters
Tao Tang, Chengzhu Yang, Tianrang Xie, Yining Liu, Lijun Xu, Desheng Chen   +5 more
openaire   +4 more sources