利用Sigmoid激活函数在CMOS上实现神经元

Shiwei Xing, Chenjian Wu
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引用次数: 6

摘要

提出了一种具有高精度Sigmoid激活函数的多输入神经元电路。该电路由输入信号加权电路、电流-电压转换电路和Sigmoid AF拟合电路组成。设计的电路可以根据差分对的电流-电压关系拟合Sigmoid函数。采用台积电0.18 um CMOS技术对电路进行了仿真。后置仿真表明,Sigmoid AF拟合电路输出与理想Sigmoid函数的误差为1.76%. The area of the layout is $375\ \mu m \times 238\ \mu m$. The maximum error caused by noise in the output of the circuit is $80\ pA/\sqrt{Hz}$.
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of A Neuron Using Sigmoid Activation Function with CMOS
A multi-input neuron circuit with high-precision Sigmoid activation function (AF) is presented in this paper. The proposed circuit composed of input signal weighting circuit, current-voltage conversion circuit, and Sigmoid AF fitting circuit. Designed circuit can fit Sigmoid function based on the current-voltage relationship of differential pairs. The circuit is simulated in TSMC 0.18 um CMOS technology. The post-simulation shows that the error between the output of Sigmoid AF fitting circuit and the ideal Sigmoid function is 1.76%. The area of the layout is $375\ \mu m \times 238\ \mu m$. The maximum error caused by noise in the output of the circuit is $80\ pA/\sqrt{Hz}$.
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