Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Vasile V Moca"'
Autor:
Cécile Gal, Ioana Țincaș, Vasile V. Moca, Andrei Ciuparu, Emanuela L. Dan, Marie L. Smith, Teodora Gliga, Raul C. Mureșan
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Recognising objects is a vital skill on which humans heavily rely to respond quickly and adaptively to their environment. Yet, we lack a full understanding of the role visual information sampling plays in this process, and its relation to th
Externí odkaz:
https://doaj.org/article/ab708246006a4c0cb3827e9690ca9155
Publikováno v:
PLoS ONE, Vol 6, Iss 7, p e22831 (2011)
Mechanisms of explicit object recognition are often difficult to investigate and require stimuli with controlled features whose expression can be manipulated in a precise quantitative fashion. Here, we developed a novel method (called "Dots"), for ge
Externí odkaz:
https://doaj.org/article/ca178877fbc94a86a42c8a18c3795a0c
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-18 (2021)
Identifying the frequency, temporal location, duration, and amplitude of finite oscillation packets in neurophysiological signals with high precision is challenging. The authors present a method based on multiple wavelets to improve the detection of
Externí odkaz:
https://doaj.org/article/3967b4594a3d46c7ab154729f6324cb7
Autor:
George F Grosu, Alexander V Hopp, Vasile V Moca, Harald Bârzan, Andrei Ciuparu, Maria Ercsey-Ravasz, Mathias Winkel, Helmut Linde, Raul C Mureșan
Publikováno v:
Cerebral Cortex. 33:4574-4605
The past 40 years have witnessed extensive research on fractal structure and scale-free dynamics in the brain. Although considerable progress has been made, a comprehensive picture has yet to emerge, and needs further linking to a mechanistic account
Autor:
Andreea Sălăgean, Andreea-Mădălina Pașc, Eugen Richard Ardelean, Raul C. Mureșan, Vasile V. Moca, Mihaela Dînșoreanu, Rodica Potolea, Camelia Lemnaru
Publikováno v:
2022 IEEE 18th International Conference on Intelligent Computer Communication and Processing (ICCP).
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-18 (2021)
Nature Communications
Nature Communications
Due to the Heisenberg–Gabor uncertainty principle, finite oscillation transients are difficult to localize simultaneously in both time and frequency. Classical estimators, like the short-time Fourier transform or the continuous-wavelet transform op
Publikováno v:
2020 28th European Signal Processing Conference (EUSIPCO)
The Continuous Wavelet Transform (CWT) provides a multi-resolution representation of a signal by scaling a mother wavelet and convolving it with the signal. The scalogram (squared modulus of the CWT) then represents the spread of the signal's energy
Time-frequency analysis is ubiquitous in many fields of science. Due to the Heisenberg-Gabor uncertainty principle, a single measurement cannot estimate precisely the location of a finite oscillation in both time and frequency. Classical spectral est
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91ab249817828072efd6dbd7bbf9a2c4
Autor:
Camelia Lemnaru, Vasile V. Moca, Mihaela Dinsoreanu, Alexander Stanciu, Eugen-Richard Ardelean, Rodica Potolea
Publikováno v:
2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP)
ICCP
ICCP
Overlapping clusters and different density clusters are recurrent phenomena of neuronal datasets, because of how neurons fire. We propose a clustering method that is able to identify clusters of arbitrary shapes, having different densities, and poten
Publikováno v:
Computer Methods and Programs in Biomedicine. 95:191-202
We investigated the problem of automatic depth of anesthesia (DOA) estimation from electroencephalogram (EEG) recordings. We employed Time Encoded Signal Processing And Recognition (TESPAR), a time-domain signal processing technique, in combination w