Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Saeed Pouryazdian"'
Autor:
Saeed Pouryazdian
Electroencephalogram (EEG) is widely used for monitoring, diagnosis purposes and also for study of brains physiological, mental and functional abnormalities. EEG is known to be a high-dimensional signal in which processing of information by the brain
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a055765c70a9b86a537fa84b1ea79ae
https://doi.org/10.32920/ryerson.14657721
https://doi.org/10.32920/ryerson.14657721
Publikováno v:
Digital Signal Processing. 48:12-26
Canonical Decomposition (CANDECOMP) also known as Parallel Factor Analysis (PARAFAC) is a well-known multiway model in high-dimensional data modeling. Approaches that use CANDECOMP/PARAFAC for parametric modeling of a noisy observation require an est
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8287263c4e262e5403ac525db109ba76
https://doi.org/10.1016/j.dsp.2015.08.014
https://doi.org/10.1016/j.dsp.2015.08.014
Autor:
Soosan Beheshti, Sridhar Krishnan, Saeed Pouryazdian, Laurel J. Trainor, Andrew Chang, Daniel J. Bosnyak
Publikováno v:
EMBC
MisMatch Negativity (MMN) is a small event-related potential (ERP) that provide an index of sensory learning and perceptual accuracy for the cognitive research. Group-level analysis plays an important role for detecting differences at group or condit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7da1dd9ae79c33c5137412573dd19209
https://pubmed.ncbi.nlm.nih.gov/28268635
https://pubmed.ncbi.nlm.nih.gov/28268635
Autor:
Saeed Pouryazdian, Teodiano Bastos, Richard M. G. Tello, Sridhar Krishnan, Soosan Beheshti, André Ferreira
Publikováno v:
EMBC
This paper presents a new way for automatic detection of SSVEPs through correlation analysis between tensor models. 3-way EEG tensor of channel × frequency × time is decomposed into constituting factor matrices using PARAFAC model. PARAFAC analysis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13cb2bfe308e25d0933b3d6a0dd6cd15
https://doi.org/10.1109/embc.2015.7319802
https://doi.org/10.1109/embc.2015.7319802
Publikováno v:
EMBC
Electroencephalogram (EEG) is widely used for monitoring, diagnosis purposes and also for study of brain's physiological, mental and functional abnormalities. Processing of information by the brain is reflected in dynamical changes of the electrical
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::08e9e001b65c4c8c2e41060a010c3e8a
https://doi.org/10.1109/embc.2015.7318313
https://doi.org/10.1109/embc.2015.7318313
Publikováno v:
ISSPA
The l p -norm regularized least square technique has been effectively exploited for sparse reconstruction problems. However, the choice of an optimum regularization parameter in the optimization routine still remains a challenge. In this paper we pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9fa2535dc14b73ba8edb229a8d505b83
https://doi.org/10.1109/isspa.2012.6310502
https://doi.org/10.1109/isspa.2012.6310502