Optimizing low-frequency common spatial pattern features for multi-class classification of hand movement directions

Author(s):  
Andrew Keong Ng ◽  
Kai Keng Ang ◽  
Keng Peng Tee ◽  
Cuntai Guan
2017 ◽  
Vol 44 (6) ◽  
pp. 587-594
Author(s):  
Sang-Hoon Park ◽  
Ha-Young Kim ◽  
David Lee ◽  
Sang-Goog Lee

2014 ◽  
Vol 926-930 ◽  
pp. 1814-1817
Author(s):  
Yu Yu Gao

For extracting relatively stable and invariable feature from non-stationary EEG in mult-class pattern, many scholars study a feature extraction method, which is called as modified multi-classcommon spatial pattern. It adopts one-to-one strategy to expand common spatial pattern to multi-class classification. While for the solution of airspace filter, Kullback-Leibler distance defines pattern of discrimination of minimize difference within class and maximize difference between classes. And it establishes a function to measure difference within the class. The experiment verifies that the algorithm can obtain feature information with recognition capability which implys in the non-stationary EEG and acquires preferable classification result.


IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 27873-27884 ◽  
Author(s):  
Thanh Nguyen ◽  
Imali Hettiarachchi ◽  
Amin Khatami ◽  
Lee Gordon-Brown ◽  
Chee Peng Lim ◽  
...  

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