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A transfer learning algorithm based on csp regularizations of recorded eeg for between-subject classiftcation
, Article 26th National and 4th International Iranian Conference on Biomedical Engineering, ICBME 2019, 27 November 2019 through 28 November 2019 ; 2019 , Pages 199-203 ; 9781728156637 (ISBN) ; Hajipour Sardouie, S ; Mohammad, H ; Foroughmand Aarabi ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
Feature extraction and classification are the most important parts of BCI systems. The new branch of BCI studies focuses on the design of a classifier that is trained to function properly for each individual. This problem is known as Transfer Learning. In between-subject classification, due to the differences in the neural signals' distribution of different individuals, using the common methods of feature extraction for training the classifier, does not lead to high accuracy for the test subject. As a result, in this study, we present a method for extracting features that perform well in between subjects classifications. The data that we used in this study are EEG signals recorded during...