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A Perceptron Circuit with DAC-based Multiplier for Sensor Analog Front-ends

机译:具有基于DAC的乘法器的Perceptron电路,用于传感器模拟前端

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This paper presents a perceptron circuit which can be implemented into sensor analog front-end consistent with neural network-based machine learning. We introduce a DAC-based multiplier in the perceptron circuit, where the DAC is used as a programmable resistor. Compared with a traditional transconductor-based multiplier, the precision of our multiplier is formulated only by the digital codes, and it has a wide input range and a good temperature dependency. The simulation result demonstrates the DAC-based multiplier amplifies smoothly analog signals by the digital codes.
机译:本文介绍了一个Perceptron电路,它可以实现成与基于神经网络的机器学习的传感器模拟前端。我们在Perceptron电路中引入基于DAC的乘法器,其中DAC用作可编程电阻。与传统的基于跨导体的乘法器相比,我们的乘法器的精度仅由数字代码配制,并且它具有宽的输入范围和良好的温度依赖性。仿真结果表明,基于DAC的乘法器通过数字代码进行平滑的模拟信号放大。

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