Genetic algorithm based feature selection for target detection in SAR images

2003 ◽  
Vol 21 (7) ◽  
pp. 591-608 ◽  
Author(s):  
Bir Bhanu ◽  
Yingqiang Lin
2020 ◽  
Vol 16 (2) ◽  
Author(s):  
Stanisław Karkosz ◽  
Marcin Jukiewicz

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.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 139512-139528
Author(s):  
Shuangjie Li ◽  
Kaixiang Zhang ◽  
Qianru Chen ◽  
Shuqin Wang ◽  
Shaoqiang Zhang

2008 ◽  
Vol 52 (9) ◽  
pp. 4380-4394 ◽  
Author(s):  
Christelle Reynès ◽  
Robert Sabatier ◽  
Nicolas Molinari ◽  
Sylvain Lehmann

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