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Fractional-Order Mihalas–Niebur Neuron Model Implementation Using Current-Mirrors

机译:使用电流镜的分数阶Mihalas–Niebur神经元模型实现

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A simple realization of the fractional-order Mihalas-Niebur neuron model is presented in this work. The required low-pass filter is implemented using current-mirrors offering simple circuitry and, also, electronic tunability of the realized time-constant. Due to the limited bandwidth required for this application, the necessary fractional-order capacitor is realized using an appropriately configured second-order RC network. The proposed realization highlights the connection between the fractional-order and the frequency spiking of the model through appropriate simulation results, which are derived via the Analog Design Environment of Cadence software, using MOS transistor models provided by the AMS 0.35μm process.
机译:这项工作提出了分数阶Mihalas-Niebur神经元模型的简单实现。所需的低通滤波器是使用电流镜实现的,该电流镜提供了简单的电路,并且还实现了所实现的时间常数的电子可调性。由于此应用所需的带宽有限,因此使用适当配置的二阶RC网络可实现必要的分数阶电容器。拟议的实现通过适当的仿真结果突出了模型的分数阶和频率峰值之间的联系,这些仿真结果是使用AMS0.35μm工艺提供的MOS晶体管模型通过Cadence软件的模拟设计环境得出的。

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