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    政大機構典藏 > 商學院 > 資訊管理學系 > 期刊論文 >  Item 140.119/46714


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    题名: A Guide for the Upper Bound on the Number of Continuous-Valued Hidden Nodes of a Feed-Forward Network
    作者: 蔡瑞煌
    Tsaih,Rua-Huan;Wan,Yat-wah
    关键词: Bound;hidden nodes;single-hidden layer feed-forward neural network;preimage;parity problem
    日期: 2010-01
    上传时间: 2010-10-06 11:40:01 (UTC+8)
    摘要: This study proposes and validates a construction concept for the realization of a real-valued single-hidden layer feed-forward neural network (SLFN) with continuous-valued hidden nodes for arbitrary mapping problems. The proposed construction concept says that for a specific application problem, the upper bound on the number of used hidden nodes depends on the characteristic of adopted SLFN and the observed properties of collected data samples. A positive validation result is obtained from the experiment of applying the construction concept to the m-bit parity problem learned by constructing two types of SLFN network solutions.
    關聯: 19th International Conference on Artificial Neural Networks (ICANN2009)
    Lecture Notes in Computer Science,5768,658-667
    数据类型: article
    DOI 連結: http://dx.doi.org/10.1007/978-3-642-04274-4_68
    DOI: 10.1007/978-3-642-04274-4_68
    显示于类别:[資訊管理學系] 期刊論文

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