Výsledky vyhledávání - "Prasad, Girijesh"

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Predicting feature imputability in the absence of ground truth

Autor: McCombe, Niamh, Ding, Xuemei, Prasad, Girijesh, Finn, David P., Todd, Stephen, McClean, Paula L., Wong-Lin, KongFatt

Data imputation is the most popular method of dealing with missing values, but in most real life applications, large missing data can occur and it is difficult or impossible to evaluate whether data has been imputed accurately (lack of ground truth).

Externí odkaz: http://arxiv.org/abs/2007.07052

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Computational neurology: Computational modeling approaches in dementia

Autor: Wong-Lin, KongFatt, Sanchez-Bornot, Jose M., McCombe, Niamh, Kaur, Daman, McClean, Paula L., Zou, Xin, Youssofzadeh, Vahab, Ding, Xuemei, Bucholc, Magda, Yang, Su, Prasad, Girijesh, Coyle, Damien, Maguire, Liam P., Wang, Haiying, Wang, Hui, Atiya, Nadim A. A., Joshi, Alok

Dementia is a collection of symptoms associated with impaired cognition and impedes everyday normal functioning. Dementia, with Alzheimer's disease constituting its most common type, is highly complex in terms of etiology and pathophysiology. A more

Externí odkaz: http://arxiv.org/abs/2005.02214

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Covariate Shift Estimation based Adaptive Ensemble Learning for Handling Non-Stationarity in Motor Imagery related EEG-based Brain-Computer Interface

Autor: Raza, Haider, Rathee, Dheeraj, Zhou, ShangMing, Cecotti, Hubert, Prasad, Girijesh

Publikováno v: Neurocomputing 2018

The non-stationary nature of electroencephalography (EEG) signals makes an EEG-based brain-computer interface (BCI) a dynamic system, thus improving its performance is a challenging task. In addition, it is well-known that due to non-stationarity bas

Externí odkaz: http://arxiv.org/abs/1805.01044

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