COMPARISON OF FOUR CLASSIFICATION METHODS FOR BRAIN-COMPUTER INTERFACE
نویسندگان
چکیده
منابع مشابه
Comparison of Four Classification Methods for Brain-computer Interface
This paper examines the performance of four classifiers for Brain Computer Interface (BCI) systems based on multichannel EEG recordings. The classifiers are designed to distinguish EEG patterns corresponding to performance of several mental tasks. The first one is the basic Bayesian classifier (BC) which exploits only interchannel covariance matrices corresponding to different mental tasks. The...
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Brain-computer interfaces (BCI) record brain signals, analyze and translate them into control commands which are relayed to output devices that carry out desired actions. These systems do not use normal neuromuscular output pathways. Actually, the principal goal of BCI systems is to provide better life style for physically-challenged people which are suffered from cerebral palsy, amyotrophic l...
متن کاملcomparison of different linear filter design methods for handling ocular artifacts in brain computer interface system
brain-computer interfaces (bci) record brain signals, analyze and translate them into control commands which are relayed to output devices that carry out desired actions. these systems do not use normal neuromuscular output pathways. actually, the principal goal of bci systems is to provide better life style for physically-challenged people which are suffered from cerebral palsy, amyotrophic la...
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In this paper, we investigate the accuracy of linear classification techniques for a P300 Brain-Computer Interface used in a typing paradigm. Fisher’s Linear Discriminant Analysis (LDA), Bayesian Linear Discriminant Analysis (BLDA), Stepwise Linear Discriminant Analysis (SLDA), linear Support Vector Machine (SVM) and a method based on Feature Extraction (FE) were compared. Experiments were perf...
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ژورنال
عنوان ژورنال: Neural Network World
سال: 2011
ISSN: 1210-0552,2336-4335
DOI: 10.14311/nnw.2011.21.007