FENG Fangchen
FENG Fangchen
Laboratoire Astroparticule & Cosmologie
Bestätigte E-Mail-Adresse bei apc.in2p3.fr - Startseite
TitelZitiert vonJahr
Hybrid model and structured sparsity for under-determined convolutive audio source separation
F Feng, M Kowalski
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
112014
An unified approach for blind source separation using sparsity and decorrelation
F Feng, M Kowalski
2015 23rd European Signal Processing Conference (EUSIPCO), 1736-1740, 2015
92015
Revisiting sparse ICA from a synthesis point of view: Blind Source Separation for over and underdetermined mixtures
F Feng, M Kowalski
Signal Processing 152, 165-177, 2018
52018
Sparsity and low-rank amplitude based blind source separation
F Feng, M Kowalski
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
52017
Vers une approche unifiée pour la séparation aveugle de sources en sur et sous-déterminé, basée sur la parcimonie et la décorrélation
F Feng, M Kowalski
32015
Underdetermined Reverberant Blind Source Separation: Sparse Approaches for Multiplicative and Convolutive Narrowband Approximation
F Feng, M Kowalski
IEEE/ACM Transactions on Audio, Speech, and Language Processing 27 (2), 442-456, 2018
22018
Non-parametric characterization of gravitational-wave polarizations
J Flamant, P Chainais, E Chassande-Mottin, F Feng, N Le Bihan
2018 26th European Signal Processing Conference (EUSIPCO), 2658-2662, 2018
22018
Structured sparsity regularization for gravitational-wave polarization reconstruction
F Feng, E Chassande-Mottin, P Bacon, A Fraysse
2018 26th European Signal Processing Conference (EUSIPCO), 1750-1754, 2018
22018
Séparation aveugle de source: de l'instantané au convolutif
F Feng
Université Paris-Saclay, 2017
12017
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–9