神經網際計算機器的集群神經元活躍能階分佈

dc.contributor施茂祥zh_TW
dc.contributorShih, Mau-Hsiangen_US
dc.contributor.author林育賢zh_TW
dc.contributor.authorLin, Yu-Sianen_US
dc.date.accessioned2019-09-05T01:11:03Z
dc.date.available2013-8-28
dc.date.available2019-09-05T01:11:03Z
dc.date.issued2013
dc.description.abstract施茂祥博士跟蔡豐聲博士於2013年在 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 提出神經網際計算機器的模型。在這篇論文的基礎之下,我們研究其神經網際計算機器的性質,改變其中刺激輸入的強弱、單一神經元影響其他神經元之連結數、以及影響神經元有序性的機率,觀察集群神經元之活躍能階的改變,並探討在何種條件下集群神經元會產生活躍能階的不穩定態。zh_TW
dc.description.abstractIn 2013, Mau-Hsiang Shih and Feng-Sheng Tsai in IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS proposed Interneural Computing Machines. Base on Shih and Tasi's paper, we shall study the extent of stimulus input pattern, the linkages that neuron affects other neurons, the probability that controls the order of the linkage of neurons within the model,and shall see how the firing energy levels of ensembles of neurons change and find out under what conditions the unstable state of firing energy levels of ensembles of neurons occurs.en_US
dc.description.sponsorship數學系zh_TW
dc.identifierGN060040040S
dc.identifier.urihttp://etds.lib.ntnu.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dstdcdr&s=id=%22GN060040040S%22.&%22.id.&
dc.identifier.urihttp://rportal.lib.ntnu.edu.tw:80/handle/20.500.12235/101704
dc.language中文
dc.subject非線性動力學zh_TW
dc.subject機器學習zh_TW
dc.subject族群動態zh_TW
dc.subjectnonlinear dynamicsen_US
dc.subjectmachine learningen_US
dc.subjectpopulation dynamicsen_US
dc.title神經網際計算機器的集群神經元活躍能階分佈zh_TW
dc.titleFiring energy levels of ensembles of neurons in interneural computing machinesen_US

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