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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/130211


    Title: The layer effect on multi-layer cellular neural networks
    Authors: 班榮超
    Ban, Jung-Chao
    Chang, Chih-Hung
    Contributors: 應數系
    Keywords: Multi-layercellularnetworks;Topological entropy;Learning problems;Variant templates
    Date: 2013-07
    Issue Date: 2020-06-22 13:44:57 (UTC+8)
    Abstract: The present investigation elucidates how the number of layers/variance of templates influences the phenomena of multi-layer cellular neural networks (MCNNs). This study relates to learning problems for MCNNs. We show that the greater the number of templates that MCNNs adopt, the richer the phenomena that are derived, while equivalently, such neural networks are more efficient as regards the learning aspect. Additionally, the MCNNs with more layers exhibit more phenomena than the ones with fewer layers. A novel phenomenon is seen in the study of the effect of the number of layers with respect to fixed templates.
    Relation: Applied Mathematics Letters, Vol.26, No.7, pp.706-709
    Data Type: article
    DOI link: https://doi.org/10.1016/j.aml.2013.01.013
    DOI: 10.1016/j.aml.2013.01.013
    Appears in Collections:[Department of Mathematical Sciences] Periodical Articles

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