Analog Implementation of a Novel Resistive-Type Sigmoidal Neuron

An important part of any hardware implementation of artificial neural networks (ANNs) is realization of the activation function which serves as the output stage of each layer. In this work, a new NMOS/PMOS design is proposed for realizing the sigmoid function as the activation function. Transistors in the proposed neuron are biased using only one biasing voltage. By operating in both triode and saturation regions, the proposed neuron can provide an accurate approximation of the sigmoid function. The neuron circuit is designed and laid out in 90-nm CMOS technology. The proposed neuron can be potentially used in implementation of both analog and hybrid ANNs.

人工神经网络（ANNs）的任何硬件实现的一个重要部分是激活函数的实现，它作为每一层的输出级。在这项工作中，提出了一种新的NMOS/PMOS设计，用于实现作为激活函数的S型函数。所提出的神经元中的晶体管仅使用一个偏置电压进行偏置。通过在三极管区和饱和区两种状态下工作，所提出的神经元能够对S型函数进行精确逼近。该神经元电路采用90纳米CMOS技术进行设计和布局。所提出的神经元有可能用于模拟和混合人工神经网络的实现。