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題名 Realization problem of multi-layer cellular neural networks
作者 班榮超
Ban, Jung-Chao
Chang, Chih-Hung
貢獻者 應數系
關鍵詞 Multi-layer cellular neural networks ; Sofic shifts ; Learning problem ; Covering space ; Separation property ; Topological entropy
日期 2015-01
上傳時間 27-May-2020 09:02:02 (UTC+8)
摘要 This paper investigates whether the output space of a multi-layer cellular neural network can be realized via a single layer cellular neural network in the sense of the existence of finite-to-one map from one output space to the other. Whenever such realization exists, the phenomena exhibited in the output space of the revealed single layer cellular neural network is at most a constant multiple of the phenomena exhibited in the output space of the original multi-layer cellular neural network. Meanwhile, the computation complexity of a single layer system is much less than the complexity of a multi-layer system. Namely, one can trade the precision of the results for the execution time. We remark that a routine extension of the proposed methodology in this paper can be applied to the substitution of hidden spaces although the detailed illustration is omitted.
關聯 Neural Networks, Vol.70, pp.9-17
資料類型 article
DOI https://doi.org/10.1016/j.neunet.2015.06.003
dc.contributor 應數系
dc.creator (作者) 班榮超
dc.creator (作者) Ban, Jung-Chao
dc.creator (作者) Chang, Chih-Hung
dc.date (日期) 2015-01
dc.date.accessioned 27-May-2020 09:02:02 (UTC+8)-
dc.date.available 27-May-2020 09:02:02 (UTC+8)-
dc.date.issued (上傳時間) 27-May-2020 09:02:02 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/129985-
dc.description.abstract (摘要) This paper investigates whether the output space of a multi-layer cellular neural network can be realized via a single layer cellular neural network in the sense of the existence of finite-to-one map from one output space to the other. Whenever such realization exists, the phenomena exhibited in the output space of the revealed single layer cellular neural network is at most a constant multiple of the phenomena exhibited in the output space of the original multi-layer cellular neural network. Meanwhile, the computation complexity of a single layer system is much less than the complexity of a multi-layer system. Namely, one can trade the precision of the results for the execution time. We remark that a routine extension of the proposed methodology in this paper can be applied to the substitution of hidden spaces although the detailed illustration is omitted.
dc.format.extent 491060 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Neural Networks, Vol.70, pp.9-17
dc.subject (關鍵詞) Multi-layer cellular neural networks ; Sofic shifts ; Learning problem ; Covering space ; Separation property ; Topological entropy
dc.title (題名) Realization problem of multi-layer cellular neural networks
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1016/j.neunet.2015.06.003
dc.doi.uri (DOI) https://doi.org/10.1016/j.neunet.2015.06.003