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    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/18226


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    题名: Analysis of Switching Dynamics with Competing Support Vector Machine
    作者: 張洺偉;林智仁;翁久幸
    Chang, Ming-Wei;Lin, Chih-Jen;Weng, Ruby C.
    日期: 2004-05
    上传时间: 2008-12-19 14:56:55 (UTC+8)
    摘要: We present a framework for the unsupervised segmentation
    of switching dynamics using support vector machines.
    Following the architecture by Pawelzik et al., where annealed competing
    neural networks were used to segment a nonstationary time
    series, in this paper, we exploit the use of support vector machines,
    a well-known learning technique. First, a new formulation of support
    vector regression is proposed. Second, an expectation-maximization
    step is suggested to adaptively adjust the annealing parameter.
    Results indicate that the proposed approach is promising.
    關聯: IEEE Transactions on Neural Networks 15(3),720-727
    数据类型: article
    DOI 連結: http://dx.doi.org/10.1109/IJCNN.2002.1007515
    DOI: 10.1109/IJCNN.2002.1007515
    显示于类别:[統計學系] 期刊論文

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