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Sensors 2016, 16(6), 871; doi:10.3390/s16060871

Feature Selection Method Based on Neighborhood Relationships: Applications in EEG Signal Identification and Chinese Character Recognition

1
Department of Computer Science & Information Engineering, National Quemoy University, 89250 Kinmen Island, Taiwan
2
Department of Electrical Engineering, Tamkang University, 25137 New Taipei City, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editors: Steffen Leonhardt and Daniel Teichmann
Received: 18 April 2016 / Revised: 24 May 2016 / Accepted: 8 June 2016 / Published: 14 June 2016
(This article belongs to the Special Issue Noninvasive Biomedical Sensors)
View Full-Text   |   Download PDF [2449 KB, uploaded 14 June 2016]   |  

Abstract

In this study, a new feature selection algorithm, the neighborhood-relationship feature selection (NRFS) algorithm, is proposed for identifying rat electroencephalogram signals and recognizing Chinese characters. In these two applications, dependent relationships exist among the feature vectors and their neighboring feature vectors. Therefore, the proposed NRFS algorithm was designed for solving this problem. By applying the NRFS algorithm, unselected feature vectors have a high priority of being added into the feature subset if the neighboring feature vectors have been selected. In addition, selected feature vectors have a high priority of being eliminated if the neighboring feature vectors are not selected. In the experiments conducted in this study, the NRFS algorithm was compared with two feature algorithms. The experimental results indicated that the NRFS algorithm can extract the crucial frequency bands for identifying rat vigilance states and identifying crucial character regions for recognizing Chinese characters. View Full-Text
Keywords: feature selection; neighborhood relationship; EEG signal; Chinese character recognition feature selection; neighborhood relationship; EEG signal; Chinese character recognition
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zhao, Y.-X.; Chou, C.-H. Feature Selection Method Based on Neighborhood Relationships: Applications in EEG Signal Identification and Chinese Character Recognition. Sensors 2016, 16, 871.

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