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首页> 外文期刊>Neural Networks: The Official Journal of the International Neural Network Society >A generalized analog implementation of piecewise linear neuron models using CCII building blocks
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A generalized analog implementation of piecewise linear neuron models using CCII building blocks

机译:使用CCII构建块的分段线性神经元模型的广义模拟实现

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摘要

This paper presents a set of reconfigurable analog implementations of piecewise linear spiking neuron models using second generation current conveyor (CCII) building blocks. With the same topology and circuit elements, without W/L modification which is impossible after circuit fabrication, these circuits can produce different behaviors, similar to the biological neurons, both for a single neuron as well as a network of neurons just by tuning reference current and voltage sources. The models are investigated, in terms of analog implementation feasibility and costs, targeting large scale hardware implementations. Results show that, in order to gain the best performance, area and accuracy; these models can be compromised. Simulation results are presented for different neuron behaviors with CMOS 350nm technology.
机译:本文介绍了一系列使用第二代电流输送机(CCII)构建块的分段线性尖峰神经元模型的可重新配置模拟实施。 利用相同的拓扑和电路元件,在电路制造之后不可能改造,这些电路可以产生不同的行为,类似于生物神经元,用于通过调节参考电流仅用于单个神经元以及神经元网络 和电压源。 根据模拟实现可行性和成本,调查模型,针对大规模硬件实现。 结果表明,为了获得最佳性能,面积和准确性; 这些模型可能会受到损害。 具有CMOS 350nm技术的不同神经元行为的仿真结果。

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