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https://ah.lib.nccu.edu.tw/handle/140.119/130212
題名: | The learning problem of multi-layer neural networks | 作者: | 班榮超 Ban, Jung-Chao Chang, Chih-Hung |
貢獻者: | 應數系 | 關鍵詞: | Multi-layer neural networks ; Topological entropy ; Sofic shift ; Learning problem ; Linear separation | 日期: | Jan-2013 | 上傳時間: | 22-Jun-2020 | 摘要: | This manuscript considers the learning problem of multi-layer neural networks (MNNs) with an activation function which comes from cellular neural networks. A systematic investigation of the partition of the parameter space is provided. Furthermore, the recursive formula of the transition matrix of an MNN is obtained. By implementing the well-developed tools in the symbolic dynamical systems, the topological entropy of an MNN can be computed explicitly. A novel phenomenon, the asymmetry of a topological diagram that was seen in Ban, Chang, Lin, and Lin (2009) [J. Differential Equations 246, pp. 552–580, 2009], is revealed. | 關聯: | Neural Networks, Vol.46, pp.116-123 | 資料類型: | article | DOI: | https://doi.org/10.1016/j.neunet.2013.05.006 |
Appears in Collections: | 期刊論文 |
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