Vasile Vlad Moca
Vasile Vlad Moca
Transylvanian Institute of Neuroscience
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Zitiert von
Zitiert von
The oscillation score: an efficient method for estimating oscillation strength in neuronal activity
RC Muresan, OF Jurjut, VV Moca, W Singer, D Nikolic
Journal of neurophysiology 99 (3), 1333-1353, 2008
Membrane resonance enables stable and robust gamma oscillations
VV Moca, D Nikolić, W Singer, RC Mureşan
Cerebral Cortex 24 (1), 119-142, 2014
Visual exploration and object recognition by lattice deformation
VV Moca, I Ţincaş, L Melloni, RC Mureşan
PloS one 6 (7), e22831, 2011
EEG under anesthesia—Feature extraction with TESPAR
VV Moca, B Scheller, RC Mureşan, M Daunderer, G Pipa
computer methods and programs in biomedicine 95 (3), 191-202, 2009
TESPAR coding study for speaker recognition
E Lupu, VV Moca, PG Pop
The 30th session of scientific presentations “Modern technologies in the XXI …, 2003
Environment for speaker recognition using speech coding
E Lupu, V Moca, PG Pop
Proc. of Communications, 199-204, 2004
Tespar a biometric time domain approach to speaker recognition
V Moca
Acta Technica Napocensis volume47, 0
Emergence of beta/gamma oscillations: ING, PING, and what about RING?
VV Moca, RC Mureşan
BMC neuroscience 12 (1), 1-2, 2011
Real and modeled spike trains: where do they meet?
VV Moca, D Nikolić, RC Mureşan
International Conference on Artificial Neural Networks, 488-497, 2008
Properties of multivariate data investigated by fractal dimensionality
D Nikolić, VV Moca, W Singer, RC Mureşan
Journal of neuroscience methods 172 (1), 27-33, 2008
EEG processing with TESPAR for depth of anesthesia detection
VV Moca, B Scheller, RC Mureşan, M Daunderer, G Pipa
BMC Neuroscience 10 (1), 1-2, 2009
TESPAR coding method evaluation in speaker recognition experiments
VV Moca, E Lupu, PG Pop
Trends in Speech Technology Proceedings of the 3rd Conference Speech …, 2005
Space Breakdown Method A new approach for density-based clustering
ER Ardelean, A Stanciu, M Dinsoreanu, R Potolea, C Lemnaru, VV Moca
2019 IEEE 15th International Conference on Intelligent Computer …, 2019
Superlets: time-frequency super-resolution using wavelet sets
VV Moca, A Nagy-Dăbâcan, H Bârzan, RC Mureşan
BioRxiv, 583732, 2019
Discriminating legitimate oscillations from broadband transients
VV Moca, RC Mureşan
BMC neuroscience 14 (S1), P286, 2013
Probing the visual system with visual hypotheses
RC Mureşan, I Ţincaş, VV Moca, L Melloni
BMC Neuroscience 10 (S1), P356, 2009
Task predictability determines knowledge acquisition during object recognition
C Gal, VV Moca, I Tincas, ML Smith, T Gliga, RC Mureşan
PLOS Biology 15 (11), e1002618, 2019
Cumulative scientific report
VV Moca, G Medorian
Volume contents Volume 172 (2008)
Y Aihara, BS Jahromi, R Yassari, M Takahashi, RL Macdonald, S Xu, ...
Journal of Neuroscience Methods 172, 323-324, 2008
Fractional Superlets
H Bârzan, VV Moca, RC Mureșan, AM Ichim
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