Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/46714
題名: | 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 |
關鍵詞: | Bound; hidden nodes; single-hidden layer feed-forward neural network; preimage; parity problem | 日期: | Jan-2010 | 上傳時間: | 6-Oct-2010 | 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 |
資料類型: | article | DOI: | http://dx.doi.org/10.1007/978-3-642-04274-4_68 |
Appears in Collections: | 期刊論文 |
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658-667.pdf | 203.53 kB | Adobe PDF2 | View/Open |
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