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Self-organized Short-Term Memory Mechanism in Spiking Neural Network

机译:尖峰神经网络的自组织短期记忆机制

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摘要

The paper is devoted to implementation and exploration of evolutionary development of the short-term memory mechanism in spiking neural networks (SNN) starting from initial chaotic state. Short-term memory is defined here as a network ability to store information about recent stimuli in form of specific neuron activity patterns. Stable appearance of this effect was demonstrated for so called stabilizing SNN, the network model proposed by the author. In order to show the desired evolutionary behavior the network should have a specific topology determined by "horizontal" layers and "vertical" columns.
机译:本文致力于从初始混沌状态开始,在尖峰神经网络(SNN)中短期记忆机制的进化发展的实现和探索。短期记忆在这里定义为一种网络功能,可以以特定神经元活动模式的形式存储有关最近刺激的信息。对于所谓的稳定SNN(作者提出的网络模型),已经证明了这种效果的稳定出现。为了显示所需的进化行为,网络应具有由“水平”层和“垂直”列确定的特定拓扑。

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