MNIST数据库
可重构性
双稳态
乙状窦函数
人工神经网络
感知器
多层感知器
计算机科学
法布里-珀罗干涉仪
光学双稳态
激活函数
人工智能
激光器
光学
材料科学
光电子学
物理
非线性光学
电信
作者
Jasna V. Crnjanski,Isidora Teofilović,Marko Krstić,Dejan M. Gvozdić
出处
期刊:Optics Letters
[The Optical Society]
日期:2024-02-21
卷期号:49 (5): 1153-1153
摘要
In this Letter, we theoretically investigate the application of a bistable Fabry-Perot semiconductor laser under optical injection as an all-optical activation unit for multilayer perceptron optical neural networks. The proposed device is programmed to provide reconfigurable sigmoid-like activation functions with adjustable thresholds and saturation points and benchmarked on machine learning image recognition problems. Due to the reconfigurability of the activation unit, the accuracy can be increased by up to 2% simply by adjusting the control parameter of the activation unit to suit the specific problem. For a simple two-layer perceptron neural network, we achieve inference accuracies of up to 95% and 85%, for the MNIST and Fashion-MNIST datasets, respectively.
科研通智能强力驱动
Strongly Powered by AbleSci AI