Efficient Nonlinear Activation Function in Optical Neural Network

H. Zhang, L. Wan, M. Gu, X. D. Jiang, J. Thompson, H. Cai, S. Paesani, R. Santagati, A. Laing, G. Lo, D. Kwong, L. Kwek, A. Liu
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Abstract

An efficient nonlinear activation function for optical neural network is proposed and demonstrated by executing complex-valued algorithms and intensity measurement. Great learning capability are achieved by the inherent properties of the complex-valued optical neural network.
光学神经网络中的高效非线性激活函数
提出了一种有效的非线性光神经网络激活函数,并通过执行复值算法和强度测量进行了验证。复值光神经网络的固有特性使其具有很强的学习能力。
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