可重构性
光子学
计算机科学
信号处理
信号(编程语言)
数字信号处理器
硅光子学
光开关
光子集成电路
光学滤波器
数字信号处理
电子工程
光电子学
计算机硬件
材料科学
电信
工程类
程序设计语言
作者
Hailong Zhou,Yuhe Zhao,Xu Wang,Dingshan Gao,Jianji Dong,Xinliang Zhang
出处
期刊:ACS Photonics
[American Chemical Society]
日期:2020-02-05
卷期号:7 (3): 792-799
被引量:132
标识
DOI:10.1021/acsphotonics.9b01673
摘要
Photonic signal processing is essential in the optical communication and\noptical computing. Numerous photonic signal processors have been proposed, but\nmost of them exhibit limited reconfigurability and automaticity. A feature of\nfully automatic implementation and intelligent response is highly desirable for\nthe multipurpose photonic signal processors. Here, we report and experimentally\ndemonstrate a fully self-learning and reconfigurable photonic signal processor\nbased on an optical neural network chip. The proposed photonic signal processor\nis capable of performing various functions including multichannel optical\nswitching, optical multiple-input-multiple-output descrambler and tunable\noptical filter. All the functions are achieved by complete self-learning. Our\ndemonstration suggests great potential for chip-scale fully programmable\noptical signal processing with artificial intelligence.\n
科研通智能强力驱动
Strongly Powered by AbleSci AI