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Optical–electronic hybrid Fourier convolutional neural network based on super-pixel complex-valued modulation

Authors :
Li Fan
Xilin Long
Jun Dai
Chong Li
Xiaowen Dong
Jian-Jun He
Source :
Applied Optics. 62:1337
Publication Year :
2023
Publisher :
Optica Publishing Group, 2023.

Abstract

An optical–electronic hybrid convolutional neural network (CNN) system is proposed and investigated for its parallel processing capability and system design robustness. It is regarded as a practical way to implement real-time optical computing. In this paper, we propose a complex-valued modulation method based on an amplitude-only liquid-crystal-on-silicon spatial light modulator and a fixed four-level diffractive optical element. A comparison of computational results of convolutions between different modulation methods in the Fourier plane shows the feasibility of the proposed complex-valued modulation method. A hybrid CNN model with one convolutional layer of multiple channels is proposed and trained electrically for different classification tasks. Our simulation results show that this model has a classification accuracy of 97.55% for MNIST, 88.81% for Fashion MNIST, and 56.16% for Cifar10, which outperforms models using only amplitude or phase modulation and is comparable to the ideal complex-valued modulation method.

Details

ISSN :
21553165 and 1559128X
Volume :
62
Database :
OpenAIRE
Journal :
Applied Optics
Accession number :
edsair.doi...........d937d116df915f060b7dbc71b022b0eb
Full Text :
https://doi.org/10.1364/ao.478540