Implementation of a Spiking Neuron in CMOS

Iman Burman, Archita Hore, Ayan Chakraborty, Sharba Bandyopadhyay, S. Chakrabarti
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引用次数: 3

Abstract

A spiking neuronal network consumes very low power for computation contrary to conventional Von-Neumann architectures. A CMOS based circuit which includes several features of a spiking neuron closely, is presented in this paper. Features such as refractory period, spike height and width, resting potential, spiking threshold, spike frequency adaptation and inter spike interval (ISI) have been incorporated in the circuit. A small set of parameters, chosen carefully control these features in the circuit response. The spiking pattern of the proposed circuit has been matched with selected experimental data of real biological neurons from Allen Institute for Brain Science (AIBS) database.
脉冲神经元在CMOS中的实现
与传统的冯-诺伊曼结构相反,尖峰神经元网络的计算功耗非常低。本文提出了一种基于CMOS的电路,它紧密地结合了尖峰神经元的几个特征。不应期、尖峰高度和宽度、静息电位、尖峰阈值、尖峰频率适应和尖峰间间隔(ISI)等特征已被纳入电路中。精心选择的一小组参数控制着电路响应中的这些特性。该电路的峰值模式与Allen脑科学研究所(AIBS)数据库中选定的真实生物神经元实验数据相匹配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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