油藏计算
计算机科学
水准点(测量)
光子学
拓扑(电路)
网络拓扑
联轴节(管道)
分布式计算
航程(航空)
光学(聚焦)
并行计算
计算机工程
电子工程
计算机网络
工程类
电气工程
材料科学
物理
人工智能
人工神经网络
光电子学
机械工程
大地测量学
光学
航空航天工程
循环神经网络
地理
作者
Lina Jaurigue,Elizabeth Robertson,Janik Wolters,Kathy Lüdge
摘要
Photonic reservoir computing is an emerging topic due to the possibility to realize very fast devices with minimal training effort. We will discuss the reservoir computing performance of memory cells with a focus on the impact of delay lines and the interplay between coupling topology and performance for various benchmark tasks. We will further show that additional delayed input can be beneficial for reservoir computing setups in general, as it provides an easy tuning parameter, which can improve the performance of a reservoir on a range of tasks.
科研通智能强力驱动
Strongly Powered by AbleSci AI