Laser & Optoelectronics Progress, Volume. 58, Issue 8, 0820001(2021)
Modeling Method of Miniaturized Nonlinear All-Optical Diffraction Deep Neural Network Based on 10.6 μm Wavelength
One method used for modeling a miniaturized nonlinear all-optical diffraction deep neural network based on 10.6 μm wavelength is proposed. First, a carbon dioxide (CO2) laser light source with a wavelength of 10.6 μm is used, and the corresponding physical size of the neural network is 1 mm×1 mm. Second, the model framework of the nonlinear all-optical diffraction deep neural network based on 10.6 μm wavelength is constructed according to the characteristics of relevant optical physical parameters. Finally, the grid search method is used to determine the hyper-parameters of the optimal neural network model, and the cross entropy loss function and the Adam optimizer are selected to optimize the neural network. The proposed method is tested on the MNIST handwritten digital dataset and the Fashion-MNIST dataset, respectively, and the classification results reach 0.9630 and 0.8743, respectively. The proposed method provides theoretical reference for the preparation of miniaturized all-optical diffraction gratings.
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Yichen Sun, Mingli Dong, Mingxin Yu, Jiabin Xia, Xu Zhang, Yuchen Bai, Lidan Lu, Lianqing Zhu. Modeling Method of Miniaturized Nonlinear All-Optical Diffraction Deep Neural Network Based on 10.6 μm Wavelength[J]. Laser & Optoelectronics Progress, 2021, 58(8): 0820001
Category: Optics in Computing
Received: Sep. 29, 2020
Accepted: Nov. 5, 2020
Published Online: Apr. 16, 2021
The Author Email: Dong Mingli (dongml@bistu.edu.cn), Yu Mingxin (yumingxin@bistu.edu.cn)