ASIA unversity:Item 310904400/9552
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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/9552


    Title: Hurst Exponents and Linear Regression with an Application to Low-Power Beta Characterization in meditation EEG
    Authors: Kang-Ming Chang;Pei-Chen Lo
    Keywords: Beta rhythm EEG;Hurst exponent;meditation;regression-fitting;wavelet
    Date: 2005-06
    Issue Date: 2010-05-12 01:12:13 (UTC+0)
    Publisher: Asia University
    Abstract: A lever-like EEG feature-extraction method based on the Hurst exponent and regression-fitting errors is proposed for identifying beta rhythms. The proposed method is superior to most methods using the time- and frequency-domain feature extraction parameters for identifying beta rhythms.
    Relation: American Journal of Electroneurodiagnostic Technology 45(2): 130-138
    Appears in Collections:[Department of Photonics and Communication Engineering] Journal Article

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