FitzHugh-Nagumo神经元模型的现场可编程模拟阵列电路实现

2007 50th Midwest Symposium on Circuits and Systems Pub Date : 2007-08-01 DOI:10.1109/MWSCAS.2007.4488691

Jun Zhao, Yong-Bin Kim

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引用次数: 26

摘要

一种简单的神经元模型FitzHugh-Nagumo (FHN)模型在现场可编程模拟阵列(FPAAs)上实现。通过对fpaa可重构电压模型电路进行算术运算，得到了该模型的微分方程。仿真和实现结果表明，FPAA是实时或快几个数量级的神经元硬件实现的可行候选。

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Circuit implementation of FitzHugh-Nagumo neuron model using Field Programmable Analog Arrays

A simple neuron model, the FitzHugh-Nagumo (FHN) model, is implemented on field programmable analog arrays (FPAAs). The differential equations of the model is integrated by making arithmetic operations on the reconfigurable voltage model circuits of the FPAAs. The simulation and implementation results demonstrate that FPAA is the viable candidate for the neuron hardware implementation in real time or many orders of magnitude faster.

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2007 50th Midwest Symposium on Circuits and Systems

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