Genetic Feature Selection for a P300 Brain Computer Interface

2015 ◽  
pp. 603-606 ◽  
Author(s):  
Y. V. Atum ◽  
J. A. Biurrun Manresa ◽  
L. Rufiner ◽  
R. C. Acevedo
Keyword(s):  
Feature Selection ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Genetic Feature ◽  
Selection For ◽  
Genetic Feature Selection

Feature selection for classification in Steady state visually evoked potentials (SSVEP)-based brain-computer interfaces with genetic algorithm

2020 ◽  
Vol 16 (2) ◽  
Author(s):  
Stanisław Karkosz ◽  
Marcin Jukiewicz
Keyword(s):  
Genetic Algorithm ◽  
Feature Selection ◽  
Steady State ◽  
Brain Computer Interface ◽  
Morphological Features ◽  
Computer Interface ◽  
Visually Evoked Potentials ◽  
Computer Interfaces ◽  
Subject Variability ◽  
Selection For

AbstractObjectivesOptimization of Brain-Computer Interface by detecting the minimal number of morphological features of signal that maximize accuracy.MethodsSystem of signal processing and morphological features extractor was designed, then the genetic algorithm was used to select such characteristics that maximize the accuracy of the signal’s frequency recognition in offline Brain-Computer Interface (BCI).ResultsThe designed system provides higher accuracy results than a previously developed system that uses the same preprocessing methods, however, different results were achieved for various subjects.ConclusionsIt is possible to enhance the previously developed BCI by combining it with morphological features extraction, however, it’s performance is dependent on subject variability.

A Novel Deep Learning Classifier and Genetic Algorithm based Feature Selection for Hybrid EEG-fNIRS Brain-Computer Interface

2020 ◽  
Vol 18 (9) ◽  
pp. 125-134
Author(s):  
T.V. Padmavathy ◽  
M. Pravin Kumar ◽  
M. Shakunthala ◽  
M.N. Vimal Kumar ◽  
S. Saravanan
Keyword(s):  
Genetic Algorithm ◽  
Feature Selection ◽  
Deep Learning ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Learning Classifier ◽  
Selection For

Genetic Feature Selection for Software Defect Prediction

2014 ◽  
Vol 20 (1) ◽  
pp. 239-244 ◽  
Author(s):  
Romi Satria Wahono ◽  
Nanna Suryana Herman
Keyword(s):  
Feature Selection ◽  
Defect Prediction ◽  
Software Defect Prediction ◽  
Software Defect ◽  
Genetic Feature ◽  
Selection For ◽  
Genetic Feature Selection

scholarly journals Genetic feature selection for texture classification

2004 ◽  
Vol 7 (3) ◽  
pp. 162-166 ◽  
Author(s):  
Pan Li ◽  
Zheng Hong ◽  
Zhang Zuxun ◽  
Zhang Jianqing
Keyword(s):  
Feature Selection ◽  
Texture Classification ◽  
Genetic Feature ◽  
Selection For ◽  
Genetic Feature Selection
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