Denoising in Mode Conversion by Utilizing Diffractive Deep Neural Networks Optimized with Reinforcement Learning.

Zheng Li, Wenbo Zhang, Yang Wang,Guanju Peng,Zongze Li,Xiaoyan Zhou,Lin Zhang

Optical Fiber Communications Conference and Exhibition（2024）

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摘要

We propose a reinforcement-learning-optimized nonlinear physical diffractive neural network, which can simultaneously perform OAM-mode and LP-mode conversion with Gaussian noise removal. The PSNR and SSIM of the converted modes reach 27.94 dB and 0.838, respectively.

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关键词

Neural Network,Denoising,Mode Conversion,Gaussian Noise,Peak Signal-to-noise Ratio,Physical Network,Nonlinear Network,Nonlinear Neural Networks,Loss Function,Nonlinear Function,Optical Fiber,Image Classification,Input Modalities,Machine Learning Framework,Orbital Angular Momentum,Output Mode,Deep Q-learning,Phase Plate

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