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Linking non-binned spike train kernels to several existing spike train metrics

机译:将非绑定的峰值训练内核链接到几个现有的峰值训练指标

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摘要

This work presents two kernels which can be applied to sets of spike times. This allows the use of state-of-the-art classification techniques to spike trains. The presented kernels are closely related to several recent and often used spike train metrics. One of the main advantages is that it does not require the spike trains to be binned. A high temporal resolution is thus preserved which is needed when temporal coding is used. As a test of the classification possibilities a jittered spike train template classification problem is solved.
机译:这项工作提出了两个内核,可以应用于峰值时间集。这允许使用最先进的分类技术来增加列车速度。提出的内核与几个最近的和经常使用的峰值训练指标密切相关。主要优点之一是它不需要对尖峰轮进行分类。因此,保留了高时间分辨率,这是使用时间编码时所需要的。作为分类可能性的测试,解决了抖动尖峰火车模板分类问题。

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