[1] Hu Chenchen, Wang Haixian,. Application of regularized logistic regressionfor movement-related potentials-based EEG classification [J]. Journal of Southeast University (English Edition), 2013, 29 (1): 38-42. [doi:10.3969/j.issn.1003-7985.2013.01.008]

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Application of regularized logistic regressionfor movement-related potentials-based EEG classification()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

29

Issue:

2013 1

Page:

38-42

Research Field:

Computer Science and Engineering

Publishing date:

2013-03-20

Info

Title:

Application of regularized logistic regressionfor movement-related potentials-based EEG classification

Author(s):

Hu Chenchen;  Wang Haixian

Research Center for Learning Science, Southeast University, Nanjing 210096, China

Keywords:

logistic regression;  locality preserving projection regularization;  electroencephalogram

PACS:

TP391

DOI:

10.3969/j.issn.1003-7985.2013.01.008

Abstract:

In order to improve classification accuracy, the regularized logistic regression is used to classify single-trial electroencephalogram(EEG). A novel approach, named local sparse logistic regression(LSLR), is proposed. The LSLR integrates the locality preserving projection regularization term into the framework of sparse logistic regression. It tries to maintain the neighborhood information of original feature space, and, meanwhile, keeps sparsity. The bound optimization algorithm and component-wise update are used to compute the weight vector in the training data, thus overcoming the disadvantage of the Newton-Raphson method and iterative re-weighted least squares(IRLS). The classification accuracy of 80% is achieved using ten-fold cross-validation in the self-paced finger tapping data set. The results of LSLR are compared with SLR, showing the effectiveness of the proposed method.

References:

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Memo

Memo:

Biographies: Hu Chenchen(1987—), female, graduate; Wang Haixian(corresponding author), male, doctor, associate professor, hxwang@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.61075009), the Natural Science Foundation of Jiangsu Province(No.BK2011595), the Program for New Century Excellent Talents in University of China, the Qing Lan Project of Jiangsu Province.
Citation: Hu Chenchen, Wang Haixian. Application of regularized logistic regression for movement-related potentials-based EEG classification[J].Journal of Southeast University(English Edition), 2013, 29(1):38-42.[doi:10.3969/j.issn.1003-7985.2013.01.008]

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