Feature Selection Method Based on Neighborhood Relationships: Applications in EEG Signal Identification and Chinese Character Recognition
學年 104
學期 2
出版（發表）日期 2016-06-14
作品名稱 Feature Selection Method Based on Neighborhood Relationships: Applications in EEG Signal Identification and Chinese Character Recognition
作品名稱（其他語言）
著者 Yu-Xiang Zhao; Chien-Hsing Chou
單位
出版者
著錄名稱、卷期、頁數 Sensors 16(6), p.871(15 pages)
摘要 : 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.
關鍵字 feature selection;neighborhood relationship;EEG signal;Chinese character recognition
語言 en
ISSN 1424-8220
期刊性質 國外
收錄於 SCI EI
產學合作
通訊作者 Yu-Xiang Zhao
審稿制度 是
國別 CHE
公開徵稿
出版型式 ,電子版
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/107454 )