神經網際計算機器的集群神經元活躍能階分佈
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2013
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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。
In 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.
In 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.
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非線性動力學, 機器學習, 族群動態, nonlinear dynamics, machine learning, population dynamics