Tanh discrete estimate for all-opical neural network based on MZI

Ruizhen Wu, Ping Huang, Jingjing Chen, Lin Wang, Yan Wu, Mingming Wang
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Abstract

Optical neural networks (ONNs) can process information in parallel and have low energy advantages which researched more and more recently aims to replace the electrical Artificial neural networks (ANN s) solutions. The MZI with Gridnet or FFTnet can realize the convolution calculation is already proved by lots of researches. But the activation functions still have to use the DAC/ ADC to do the photoelectric conversion and then calculated in electronic-based hardware systems. We proposed a discrete estimate scheme for all-optical activation function in this paper. The scheme can give different accurate results with different implementation cost.
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基于MZI的全光神经网络Tanh离散估计
光神经网络(ONNs)具有并行处理信息和低能耗的优点,是近年来越来越多的研究旨在取代电人工神经网络(ANN)的解决方案。网格网或FFTnet的MZI可以实现卷积计算,这已经被大量的研究证明。但是在基于电子的硬件系统中,激活函数仍然需要使用DAC/ ADC进行光电转换然后计算。本文提出了一种全光激活函数的离散估计方案。在不同的实施成本下,该方案可以得到不同的精确结果。
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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