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    ASIA unversity > 資訊學院 > 資訊工程學系 > 期刊論文 >  Item 310904400/8966


    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/8966


    Title: Radial Basis Function-Based Neural Network for Harmonics Detection
    Authors: G. W. Chang;C. I Chen;Y. F. Teng
    Date: 2009
    Issue Date: 2010-04-15 13:42:30 (UTC+8)
    Abstract: The widespread application of power electronic loads has led to increasing harmonic pollution in the supply system. In order to prevent harmonics from deteriorating the power quality, detecting harmonic components for harmonic mitigations becomes a critical issue. In this paper, an effective procedure based on the radial basis function neural network is proposed to detect harmonic amplitudes of the measured signal. By comparing with several commonly used methods, it is shown that the proposed solution procedure yields more accurate results and requires less sampled data for harmonics assessment.
    Relation: IEEETransactions on Industrial Electronics
    Appears in Collections:[資訊工程學系] 期刊論文

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