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Document Type : Latin Dissertation
Language of Document : English
Record Number : 154983
Doc. No : ET26775
Main Entry : Mark John Polak
Title Proper : Adaptive Logic Networks in a Brain-Computer Interface SystemET C A L I B ~ &RIQUEMENTET C A L I B ~&RIQUEMENT.POMPES PAR TRANSITIONS MULTIPLES
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : A new parallel man-machine training approach to brain-computer interface (BCI) succeededthrough a unique application of machine learning and pattern recognition methods. The BCIsystem could train users to control m animated cursor on the computer screen by voluntaryelectroencephalogram (EEG) modulation. Our BCI system requires only two to fourelectrodes, and has a relatively short training time for both the user and the machine.Moving the cursor in one dimension, our subjects were able to hit 100 of randomlyselected targets, while in two dimensions, accuracies of approximately 86 and 62 wereaveraged in the last three sessions with our two subjects..
Subject : Electericl tess
: برق
electronic file name : TL51051.pdf
Title and statement of responsibility and : Adaptive Logic Networks in a Brain-Computer Interface SystemET C A L I B ~ &RIQUEMENTET C A L I B ~&RIQUEMENT.POMPES PAR TRANSITIONS MULTIPLES [Thesis]
 
 
 
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