Classification Of P300 Signals In Brain-Computer Interface Using Neural Networks With Adjustable Activation Functions

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Classification Of P300 Signals In Brain-Computer Interface Using Neural Networks With Adjustable Activation Functions

Brain-Computer Interface (BCI) employs brain’s Electroencephalograms (EEG) signals and Event-related potentials (ERP) such as P300 to provide a direct communication between human brain and computer. P300 speller application is a BCI that finds the location of target character using P300 signal...

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Bibliographic Details
Main Author:	Aslarzanagh, Seyed Aliakbar Mousavi
Format:	Thesis
Language:	English
Published:	2013
Subjects:	QA75.5-76.95 Electronic computers. Computer science
Online Access:	http://eprints.usm.my/43934/ http://eprints.usm.my/43934/1/Seyed%20Aliakbar%20Mousavi%20Aslarzanagh24.pdf

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