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    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/81287

    題名: Extracting the Critical Frequency Bands to Classify Vigilance States of Rats by Using a Novel Feature Selection Algorithm
    作者: Chou, Chien-Hsing;Kuo, Chung-Chih;Yu, Zong-En;Tai1, Hsien-Pang;Chen, Ke-Wei
    貢獻者: 淡江大學電機工程學系
    關鍵詞: feature selection;frequency band;pattern recognition;vigilance states
    日期: 2013-02-25
    上傳時間: 2013-03-07 16:46:08 (UTC+8)
    摘要: Identifying mammalian vigilance states has recently become an important topic in biological science research. The biological researchers concern not only to improve the accuracy rate for classifying the vigilance states, but also to extract the meaningful frequency bands. In this study, we propose a novel feature selection to extract the critical frequency bands of rat’s EEG signals. The proposed algorithm adopts the concept of neighborhood relation during adding and eliminating a candidate feature. In the experiments, the proposed method shows better accuracy rate, and find out the feature subset which locate on the critical frequency bands for recognizing rat’s vigilance states.
    關聯: 2013 2nd International Conference on Information Computer Application (ICICA 2013), 4p.
    顯示於類別:[電機工程學系暨研究所] 會議論文


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