( en | de | ru )

 

Disambiguation of "Cong, Fengyu"

Author of the publication

copydeleteadd this publication to your clipboard
Shift-Invariant Canonical Polyadic Decomposition of Complex-Valued Multi-Subject fMRI Data With a Phase Sparsity Constraint.

, , , , , and . IEEE Trans. Medical Imaging, 39 (4): 844-853 (2020)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Martha Congehl

Irene Congehl

Salvador Congost Zimmermann

Lina Cong

Daniel Congreve

 

Other publications of authors with the same name

Blind speech signal separation based on non-stationary and colored characteristics., , , , and . ISSPA, page 491-494. IEEE, (2005)Multi-domain feature analysis for depression: A study of N170 in time, frequency and spatial domains simultaneously., , , , , and . EMBC, page 5986-5989. IEEE, (2013)Discovering dynamic task-modulated functional networks with specific spectral modes using MEG., , , , , , and . NeuroImage, (2020)Discovering hidden brain network responses to naturalistic stimuli via tensor component analysis of multi-subject fMRI data., , , , , , and . NeuroImage, (2022)Stability-driven non-negative matrix factorization-based approach for extracting dynamic network from resting-state EEG., , , and . Neurocomputing, (2020)Double Coupled Canonical Polyadic Decomposition for Joint Blind Source Separation., , , and . IEEE Trans. Signal Process., 66 (13): 3475-3490 (2018)A deep learning model developed for sleep apnea detection: A multi-center study., , , , , and . Biomed. Signal Process. Control., (August 2023)Double coupled canonical polyadic decomposition of third-order tensors: Algebraic algorithm and relaxed uniqueness conditions., , , and . Signal Process. Image Commun., (2019)Dimension reduction for individual ica to decompose FMRI during real-world experiences: principal component analysis vs. canonical correlation analysis., , , , , , , and . ESANN, (2013)Data model conversion for independent component analysis to extract brain signals., and . iCAST, page 187-192. IEEE, (2011)