论文标题
基于频率多路复用的光子储层计算机
Photonic reservoir computer based on frequency multiplexing
论文作者
论文摘要
水库计算是一种用于信息处理的大脑启发方法，非常适合模拟实现。我们报告了储层计算机的光子实现，该计算机利用频域多路复用来编码神经元状态。该系统以20 MHz的速度同时处理25个梳子线（即25个神经元）。我们说明了两个标准基准任务的性能：通道均衡和时间序列预测。我们还证明了频率多路复用允许通过光学衰减在光学域中实现输出权重。我们讨论了高速高性能低足迹实现的观点。
Reservoir computing is a brain inspired approach for information processing, well suited to analogue implementations. We report a photonic implementation of a reservoir computer that exploits frequency domain multiplexing to encode neuron states. The system processes 25 comb lines simultaneously (i.e. 25 neurons), at a rate of 20 MHz. We illustrate performances on two standard benchmark tasks: channel equalization and time series forecasting. We also demonstrate that frequency multiplexing allows output weights to be implemented in the optical domain, through optical attenuation. We discuss the perspectives for high speed high performance low footprint implementations.
