NDLI: Feature selection by independent component analysis and mutual information maximization in EEG signal classification

Content Provider	IEEE Xplore Digital Library
Author	Tian Lan Erdogmus, D. Adami, A. Pavel, M.
Copyright Year	2005
Description	Author affiliation: Dept. of Biomed. Eng., Oregon Health & Sci. Univ., Beaverton, OR, USA (Tian Lan; Erdogmus, D.; Adami, A.; Pavel, M.)
Abstract	Feature selection and dimensionality reduction are important steps in pattern recognition. In this paper, we propose a scheme for feature selection using linear independent component analysis and mutual information maximization method. The method is theoretically motivated by the fact that the classification error rate is related to the mutual information between the feature vectors and the class labels. The feasibility of the principle is illustrated on a synthetic dataset and its performance is demonstrated using EEG signal classification. Experimental results show that this method works well for feature selection.
Starting Page	3011
Ending Page	3016
File Size	1532202
Page Count	6
File Format	PDF
ISBN	0780390482
DOI	10.1109/IJCNN.2005.1556405
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-07-31
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Independent component analysis Electroencephalography Pattern classification Mutual information Pattern recognition Principal component analysis Linear discriminant analysis Random variables Biomedical engineering Robustness
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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